Gustavo Carneiro
School of Computer and Mathematical Sciences
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
I have focused my research on the development and application of computer vision and machine learning techniques, with particular emphasis on medical image analysis problems. For more details on the current (and past) research problems, please check this page.
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Appointments
Date Position Institution name 2015 - ongoing Associate Professor University of Adelaide 2014 - 2015 Humboldt Experienced Researcher Technical University of Munich 2011 - 2014 Senior Lecturer University of Adelaide 2011 - 2011 Marie Curie International Incoming Fellow University of Lisbon 2008 - 2010 Visiting Assistant Professor University of Lisbon 2006 - 2008 Senior Research Scientist Siemens Corporate Research 2004 - 2005 Postdoctoral Fellow University of British Columbia 2004 - 2004 Postdoctoral Fellow University of California, San Diego -
Language Competencies
Language Competency English Can read, write, speak, understand spoken and peer review French Can read Portuguese Can read, write, speak, understand spoken and peer review Spanish; Castilian Can read and understand spoken -
Education
Date Institution name Country Title 1999 - 2004 University of Toronto Canada PhD 1997 - 1999 Instituto Militar de Engenharia Brazil MSc 1992 - 1996 Universidade Federal do Rio de Janeiro Brazil Bachelor's degree -
Research Interests
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Journals
Year Citation 2025 Cordeiro, F. R., & Carneiro, G. (2025). ANNE: Adaptive Nearest Neighbours and Eigenvector-based sample selection for robust learning with noisy labels. Pattern Recognition, 159, 10 pages.
Scopus12025 Wang, C., Liu, F., Chen, Y., Fung Kwok, C., Elliott, M., Pena-Solorzano, C., . . . Carneiro, G. (2025). Progressive Mining and Dynamic Distillation of Hierarchical Prototypes for Disease Classification and Localisation. IEEE Journal of Biomedical and Health Informatics, 1-13.
2025 Wang, Y., Song, K., Liu, Y., Ma, S., Yan, Y., & Carneiro, G. (2025). Leveraging labelled data knowledge: A cooperative rectification learning network for semi-supervised 3D medical image segmentation. Medical Image Analysis, 101, 15 pages.
2025 Wang, C., Liu, F., Chen, Y., Frazer, H., & Carneiro, G. (2025). Cross- and Intra-image Prototypical Learning for Multi-label Disease Diagnosis and Interpretation. IEEE Transactions on Medical Imaging, 1.
Scopus22025 Wang, H., Lu, N., Wang, Z., Yan, Y., Carneiro, G., & Wang, Z. (2025). Self-Correcting Clustering. IEEE Transactions on Knowledge and Data Engineering, 37(3), 1439-1454.
2024 Frazer, H. M. L., Peña-Solorzano, C. A., Kwok, C. F., Elliott, M. S., Chen, Y., Wang, C., . . . McCarthy, D. J. (2024). Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer. Nature Communications, 15(1), 7525-1-7525-12.
Scopus9 Europe PMC52024 Wang, H., Butler, D., Zhang, Y., Avery, J., Knox, S., Ma, C., . . . Carneiro, G. (2024). Human-AI collaborative multi-modal multi-rater learning for endometriosis diagnosis.. Physics in medicine and biology, 70(1), 13 pages.
Scopus1 Europe PMC12024 Tan, J. L., Pitawela, D., Chinnaratha, M. A., Beany, A., Aguila, E. J., Chen, H. T., . . . Singh, R. (2024). Exploring vision transformers for classifying early Barrett's dysplasia in endoscopic images: A pilot study on white-light and narrow-band imaging. JGH Open, 8(9), 7 pages.
2024 Liu, Y., Tian, Y., Wang, C., Chen, Y., Liu, F., Belagiannis, V., & Carneiro, G. (2024). Translation Consistent Semi-supervised Segmentation for 3D Medical Images. IEEE Transactions on Medical Imaging, 44(2), 952-968.
Scopus22024 Dadykin, I. A., Dinh, C. N., Shiel, R. J., & Kotov, A. A. (2024). Redescription of Ilyocryptus raridentatus Smirnov, 1989 (Cladocera: Ilyocryptidae). Zootaxa, 5468(2), 331-349.
Scopus12024 Kwong, J. C. C., Nguyen, D. -D., Khondker, A., Kim, J. K., Johnson, A. E. W., McCradden, M. M., . . . Rickard, M. (2024). When the Model Trains You: Induced Belief Revision and Its Implications on Artificial Intelligence Research and Patient Care — A Case Study on Predicting Obstructive Hydronephrosis in Children. NEJM AI, 1(2).
2024 Tian, Y., Zorron Cheng Tao Pu, L., Liu, Y., Maicas, G., Verjans, J. W., Burt, A. D., . . . Carneiro, G. (2024). Detecting, localizing and classifying polyps from colonoscopy videos using deep learning. Unknown Journal, 425-450.
2024 Vente, C. D., Vermeer, K. A., Jaccard, N., Wang, H., Sun, H., Khader, F., . . . Sánchez, C. I. (2024). AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.. IEEE Trans. Medical Imaging, 43, 542-557. 2024 Tapper, W., Carneiro, G., Mikropoulos, C., Thomas, S. A., Evans, P. M., & Boussios, S. (2024). The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer. Journal of Personalized Medicine, 14(3), 19 pages.
Scopus16 Europe PMC102024 Yap, M. H., Cassidy, B., Byra, M., Liao, T. Y., Yi, H., Galdran, A., . . . Kendrick, C. (2024). Diabetic foot ulcers segmentation challenge report: Benchmark and analysis. Medical Image Analysis, 94, 14 pages.
Scopus17 Europe PMC12024 Killam, L. A., Egan, R., Godfrey, C., Ross-White, A., Camargo-Plazas, P., Lock, M., & Luctkar-Flude, M. (2024). PROTOCOL: Learner-educator co-creation of student assessment in health professional education courses: A scoping review protocol. Campbell Systematic Reviews, 20(2).
Scopus12024 Muhl, C., Mulligan, K., Bayoumi, I., Ashcroft, R., Ross-White, A., & Godfrey, C. (2024). Social prescribing for children and youth: A scoping review protocol. PLoS ONE, 19(3 March), e0297535.
Scopus22024 Chen, Y., Liu, Y., Wang, C., Elliott, M., Kwok, C. F., Peña-Solorzano, C., . . . Carneiro, G. (2024). BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations. Medical Image Analysis, 96, 103192-1-103192-13.
Scopus4 Europe PMC12024 Tamirisa, K. P., Sanders, P., & Al-Ahmad, A. (2024). Understanding Atrial Fibrillation in the Context of Body Fat Distribution. JACC: Advances, 3(6), 100972.
Scopus12024 Hermoza, R., Nascimento, J. C., & Carneiro, G. (2024). Weakly-supervised preclinical tumor localization associated with survival prediction from lung cancer screening Chest X-ray images. Computerized Medical Imaging and Graphics, 115, 102395-1-102395-10.
Scopus12024 Avery, J. C., Knox, S., Deslandes, A., Leonardi, M., Lo, G., Wang, H., . . . Imagendo Study Group. (2024). Noninvasive diagnostic imaging for endometriosis part 2: a systematic review of recent developments in magnetic resonance imaging, nuclear medicine and computed tomography. Fertility and Sterility, 121(2), 189-211.
Scopus7 WoS1 Europe PMC52024 Avery, J. C., Deslandes, A., Freger, S. M., Leonardi, M., Lo, G., Carneiro, G., . . . Imagendo Study Group. (2024). Noninvasive diagnostic imaging for endometriosis part 1: a systematic review of recent developments in ultrasound, combination imaging, and artificial intelligence. Fertility and Sterility, 121(2), 164-188.
Scopus16 WoS2 Europe PMC92024 Pettman, T. L., Pontifex, K., Williams, C. P., Wildgoose, D., Dent, C., Fairbrother, G., . . . Bogomolova, S. (2024). Part Discount Grocer, Part Social Connection: Defining Elements of Social Supermarkets. Nonprofit and Voluntary Sector Quarterly, 53(5), 1306-1328.
2024 Bedrikovetski, S., Zhang, J., Seow, W., Traeger, L., Moore, J. W., Verjans, J., . . . Sammour, T. (2024). Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer. Journal of Medical Imaging and Radiation Oncology, 68(1), 33-40.
Scopus3 Europe PMC32024 Wang, C., Chen, Y., Liu, F., Elliott, M., Kwok, C. F., Pena-Solorzano, C., . . . Carneiro, G. (2024). An Interpretable and Accurate Deep-learning Diagnosis Framework Modelled with Fully and Semi-supervised Reciprocal Learning. IEEE Transactions on Medical Imaging, 43(1), 392-404.
Scopus12 Europe PMC32023 Cordeiro, F. R., Sachdeva, R., Belagiannis, V., Reid, I., & Carneiro, G. (2023). LongReMix: Robust learning with high confidence samples in a noisy label environment. Pattern Recognition, 133, 109013-1-109013-14.
Scopus632023 Vente, C. D., Vermeer, K. A., Jaccard, N., Wang, H., Sun, H., Khader, F., . . . Sánchez, C. I. (2023). AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge.. CoRR, abs/2302.01738. 2023 Hollis-Sando, L., Pugh, C., Franke, K., Zerner, T., Tan, Y., Carneiro, G., . . . Bacchi, S. (2023). Deep learning in the marking of medical student short answer question examinations: Student perceptions and pilot accuracy assessment. FOCUS ON HEALTH PROFESSIONAL EDUCATION-A MULTIDISCIPLINARY JOURNAL, 24(1), 38-48.
2023 Tian, Y., Liu, F., Pang, G., Chen, Y., Liu, Y., Verjans, J. W., . . . Carneiro, G. (2023). Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. Medical Image Analysis, 90, 102930-1-102930-11.
Scopus21 Europe PMC22023 Wang, C., Cui, Z., Yang, J., Han, M., Carneiro, G., & Shen, D. (2023). BowelNet: Joint Semantic-Geometric Ensemble Learning for Bowel Segmentation From Both Partially and Fully Labeled CT Images. IEEE Transactions on Medical Imaging, 42(4), 1225-1236.
Scopus9 Europe PMC12023 Nguyen, C., Do, T. -T., & Carneiro, G. (2023). Task Weighting in Meta-learning with Trajectory Optimisation. 2023 Nguyen, C., Do, T. -T., & Carneiro, G. (2023). Towards the Identifiability in Noisy Label Learning: A Multinomial
Mixture Approach.2023 Sachdeva, R., Cordeiro, F. R., Belagiannis, V., Reid, I., & Carneiro, G. (2023). ScanMix : Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning. Pattern Recognition, 134, 109121-1-109121-10.
Scopus25 WoS52023 Frazer, H. M. L., Tang, J. S. N., Elliott, M. S., Kunicki, K. M., Hill, B., Karthik, R., . . . McCarthy, D. J. (2023). ADMANI: Annotated Digital Mammograms and Associated Non-Image Datasets. Radiology: Artificial Intelligence, 5(2), 1-7.
Scopus19 WoS3 Europe PMC122023 Galdran, A., Verjans, J. W., Carneiro, G., & González Ballester, M. A. (2023). Multi-Head Multi-Loss Model Calibration. Lecture Notes in Computer Science, 14222, 108-117.
Scopus62023 Galdran, A., Carneiro, G., & Ballester, M. A. G. (2023). On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13797 LNCS, 40-51.
Scopus112023 De Vente, C., Vermeer, K. A., Jaccard, N., Wang, H., Sun, H., Khader, F., . . . Sanchez, C. I. (2023). AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge. IEEE Transactions on Medical Imaging, PP(1), 1.
Scopus22 Europe PMC82023 Chen, Y., Liu, Y., Wang, H., Liu, F., Wang, C., Frazer, H., & Carneiro, G. (2023). Unraveling Instance Associations: A Closer Look for Audio-Visual
Segmentation.2023 Nguyen, C., Do, T. -T., & Carneiro, G. (2023). PAC-Bayes meta-learning with implicit task-specific posteriors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1), 841-851.
Scopus3 WoS12023 Avery, J., Zhang, Y., Wang, H., O’Hara, R., Condous, G., Leonardi, M., . . . Hull, M. -L. (2023). #122 : Extrapolating Endometriosis Diagnosis Using Imaging and Machine Learning: The Imagendo Project. Fertility & Reproduction, 05(04), 527.
2023 Nguyen, C., Do, T. T., & Carneiro, G. (2023). Task Weighting in Meta-learning with Trajectory Optimisation. Transactions on Machine Learning Research, 2023.
Scopus12022 Chen, H. -T., Zhang, Y., Carneiro, G., Shin, S. H., & Singh, R. (2022). Toward a Human-Centered AI-assisted Colonoscopy System. 2022 Tan, J. L., Chinnaratha, M. A., Woodman, R., Martin, R., Chen, H. -T., Carneiro, G., & Singh, R. (2022). Diagnostic Accuracy of Artificial Intelligence (AI) to Detect Early Neoplasia in Barrett's Esophagus: A Non-comparative Systematic Review and Meta-Analysis. Frontiers in Medicine, 9, 1-11.
Scopus8 WoS2 Europe PMC62022 Oakden-Rayner, L., Gale, W., Bonham, T. A., Lungren, M. P., Carneiro, G., Bradley, A. P., & Palmer, L. J. (2022). Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study.. Lancet Digit Health, 4(5), e351-e358.
Scopus53 WoS18 Europe PMC352022 Galdran, A., Carneiro, G., & Ballester, M. Á. G. (2022). On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness.. CoRR, abs/2209.06078. 2022 Galdran, A., Hewitt, K. J., Laleh, N. G., Kather, J. N., Carneiro, G., & Ballester, M. Á. G. (2022). Test Time Transform Prediction for Open Set Histopathological Image Recognition.. CoRR, abs/2206.10033. 2022 Moura, T. C. M. S., Arruda, L. C. P. M., Silva, R. J. A. F., Silva, R. F., Oliveira, A., Tobal, L. M., . . . Guerra, M. M. P. (2022). Diluent Containing Dimethylformamide Added With Sucrose Improves <i>In Vitro</i> Quality After Freezing/Thawing Stallion Sperm. JOURNAL OF EQUINE VETERINARY SCIENCE, 109, 5 pages.
WoS32022 Frazer, H. M. L., Peña-Solorzano, C., Kwok, C. F., Elliott, M., Chen, Y., Wang, C., . . . McCarthy, D. (2022). Comparison of AI-integrated pathways with human-AI interaction for population mammographic screening.
2021 Tian, Y., Liu, F., Pang, G., Chen, Y., Liu, Y., Verjans, J. W., . . . Carneiro, G. (2021). Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation.. CoRR, abs/2109.01303. 2021 Galdran, A., Carneiro, G., & Ballester, M. Á. G. (2021). Balanced-MixUp for Highly Imbalanced Medical Image Classification.. CoRR, abs/2109.09850. 2021 Galdran, A., Carneiro, G., & Ballester, M. Á. G. (2021). Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation.. CoRR, abs/2110.01939. 2021 Galdran, A., Carneiro, G., & Ballester, M. Á. G. (2021). Convolutional Nets Versus Vision Transformers for Diabetic Foot Ulcer Classification.. CoRR, abs/2111.06894. 2021 Santiago, C., Barata, C., Sasdelli, M., Carneiro, G., & Nascimento, J. C. (2021). LOW: Training deep neural networks by learning optimal sample weights. Pattern Recognition, 110, 1-12.
Scopus25 WoS112021 Ang, T. L., & Carneiro, G. (2021). Artificial intelligence in gastrointestinal endoscopy. Journal of Gastroenterology and Hepatology (Australia), 36(1), 5-6.
Scopus12 WoS7 Europe PMC52021 David, R., Menezes, R. -J. D., De Klerk, J., Castleden, I. R., Hooper, C. M., Carneiro, G., & Gilliham, M. (2021). Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network. Scientific Reports, 11(1), 1-11.
Scopus4 WoS1 Europe PMC22021 Bedrikovetski, S., Dudi-Venkata, N. N., Maicas Suso, G., Kroon, H. M., Seow, W., Carneiro, G., . . . Sammour, T. (2021). Artificial intelligence for the diagnosis of lymph node metastases in patients with abdominopelvic malignancy: a systematic review and meta-analysis. Artificial Intelligence in Medicine, 113, 1-11.
Scopus27 WoS13 Europe PMC222021 Nguyen, L. V., Nguyen, C. C., Carneiro, G., Ebendorff-Heidepriem, H., & Warren-Smith, S. C. (2021). Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference. Photonics Research, 9(4), 109-118.
Scopus67 WoS312021 Banach, A., Strydom, M., Jaiprakash, A., Carneiro, G., Eriksson, A., Crawford, R., & McFadyen, A. (2021). Visual Localisation for Knee Arthroscopy. International Journal of Computer Assisted Radiology and Surgery, 16(12), 2137-2145.
Scopus4 WoS2 Europe PMC12021 Condon, J. J. J., Oakden-Rayner, L., Hall, K. A., Reintals, M., Holmes, A., Carneiro, G., & Palmer, L. J. (2021). Replication of an open-access deep learning system for screening mammography: Reduced performance mitigated by retraining on local data.
2021 Bedrikovetski, S., Dudi-Venkata, N. N., Kroon, H. M., Seow, W., Vather, R., Carneiro, G., . . . Sammour, T. (2021). Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis. BMC Cancer, 21(1), 1058-1-1058-10.
Scopus89 WoS27 Europe PMC702021 van der Burgt, J. M. A., Camps, S. M., Antico, M., Carneiro, G., & Fontanarosa, D. (2021). Arthroscope localization in 3D ultrasound volumes using weakly supervised deep learning. Applied Sciences, 11(15), 1-13.
2021 Maicas Suso, G., Leonardi, M., Avery, J., Panuccio, C., Carneiro, G., Hull, M. L., & Condous, G. (2021). Deep learning to diagnose pouch of Douglas obliteration with ultrasound sliding sign. Reproduction and Fertility, 2(4), 236-243.
Scopus22 WoS6 Europe PMC62021 Natusch, D. J. D., Esquerré, D., Lyons, J. A., Hamidy, A., Lemmon, A. R., Lemmon, E. M., . . . Donnellan, S. (2021). Phylogenomics, biogeography and taxonomic revision of New Guinean pythons (Pythonidae, Leiopython) harvested for international trade. Molecular Phylogenetics and Evolution, 158, 10 pages.
Scopus6 Europe PMC22020 Antico, M., Sasazawa, F., Takeda, Y., Jaiprakash, A. T., Wille, M. L., Pandey, A. K., . . . Fontanarosa, D. (2020). Bayesian CNN for Segmentation Uncertainty Inference on 4D Ultrasound Images of the Femoral Cartilage for Guidance in Robotic Knee Arthroscopy. IEEE Access, 8, 223961-223975.
Scopus19 WoS102020 Tian, Y., Maicas, G., Pu, L. Z. C. T., Singh, R., Verjans, J. W., & Carneiro, G. (2020). Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy.. CoRR, abs/2006.14811. 2020 Ranasinghe, I., Hossain, S., Ali, A., Horton, D., Adams, R. J., Aliprandi-Costa, B., . . . Woodman, R. J. (2020). SAFety, Effectiveness of care and Resource use among Australian Hospitals (SAFER Hospitals): a protocol for a population-wide cohort study of outcomes of hospital care. BMJ, 10(8), e035446-1-e035446-9.
Scopus1 WoS1 Europe PMC12020 Carneiro, G., Zorron Cheng Tao Pu, L., Singh, R., & Burt, A. (2020). Deep learning uncertainty and confidence calibration for the five-class polyp classification from colonoscopy. Medical Image Analysis, 62, 1-13.
Scopus55 WoS29 Europe PMC162020 Jonmohamadi, Y., Takeda, Y., Liu, F., Sasazawa, F., Maicas, G., Crawford, R., . . . Carneiro, G. (2020). Automatic segmentation of multiple structures in knee arthroscopy using deep learning. IEEE Access, 8, 51853-51861.
Scopus25 WoS122020 Angelova, A., Carneiro, G., Sünderhauf, N., & Leitner, J. (2020). Special Issue on Deep Learning for Robotic Vision. International Journal of Computer Vision, 128(5), 2 pages.
Scopus22020 Nascimento, J. C., & Carneiro, G. (2020). One shot segmentation: unifying rigid detection and non-rigid segmentation using elastic regularization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(12), 3054-3070.
Scopus12 WoS10 Europe PMC22020 Banach, A., Strydom, M., Jaiprakash, A., Carneiro, G., Brown, C., Crawford, R., & McFadyen, A. (2020). Saliency improvement in feature-poor surgical environments using Local Laplacian of Specified Histograms. IEEE Access, 8, 213378-213388.
Scopus2 WoS22020 Carneiro, G., Tavares, J. M. R. S., Bradley, A. P., Papa, J. P., Belagiannis, V., Nascimento, J. C., & Lu, Z. (2020). Special issue: 4<sup>th</sup> MICCAI workshop on deep learning in medical image analysis. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 8(5), 501.
Scopus12020 Cheng Tao Pu, L. Z., Maicas, G., Tian, Y., Yamamura, T., Nakamura, M., Suzuki, H., . . . Singh, R. (2020). Computer-aided diagnosis for characterisation of colorectal lesions: a comprehensive software including serrated lesions. Gastrointestinal Endoscopy, 92(4), 891-899.
Scopus38 WoS27 Europe PMC172020 Dunnhofer, M., Antico, M., Sasazawa, F., Takeda, Y., Camps, S., Martinel, N., . . . Fontanarosa, D. (2020). Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images. Medical Image Analysis, 60, 101631-1-101631-17.
Scopus67 WoS46 Europe PMC162020 Antico, M., Fontanarosa, D., Carneiro, G., Vukovic, D., Camps, S. M., Sasazawa, F., . . . Crawford, R. (2020). Deep learning for US image quality assessment based on femoral cartilage boundaries detection in autonomous knee arthroscopy. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 67(12), 2543-2552.
Scopus8 WoS5 Europe PMC12020 David, R., Menezes, R. -J., De Klerk, J., Castleden, I., Hooper, C., Carneiro, G., & Gilliham, M. (2020). Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network.
Europe PMC12020 Le, H. -S., Akmeliawati, R., & Carneiro, G. (2020). Domain Generalisation with Domain Augmented Supervised Contrastive Learning (Student Abstract).. CoRR, abs/2012.13973. 2020 Carneiro, G. F., Ferreira, M. P., & de Sá Volotão, C. F. (2020). Multi-source remote sensing data improves the classification accuracy of natural forests and eucalyptus plantations. Revista Brasileira de Cartografia, 72(1), 110-124.
Scopus12020 Liao, Z., Drummond, T., Reid, I., & Carneiro, G. (2020). Approximate Fisher information matrix to characterise the training of deep neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(1), 15-26.
Scopus18 WoS11 Europe PMC12020 Antico, M., Sasazawa, F., Dunnhofer, M., Camps, S. M., Jaiprakash, A. T., Pandey, A. K., . . . Fontanarosa, D. (2020). Deep learning-based femoral cartilage automatic segmentation in ultrasound imaging for guidance in robotic knee arthroscopy. Ultrasound in Medicine and Biology, 46(2), 422-435.
Scopus30 WoS23 Europe PMC132020 Camps, S. M., Houben, T., Carneiro, G., Edwards, C., Antico, M., Dunnhofer, M., . . . Fontanarosa, D. (2020). Automatic quality assessment of transperineal ultrasound images of the male pelvic region, using deep learning. Ultrasound in Medicine and Biology, 46(2), 445-454.
Scopus12 WoS8 Europe PMC62019 Felix, R., Harwood, B., Sasdelli, M., & Carneiro, G. (2019). Generalised zero-shot learning with a classifier ensemble over multi-modal embedding spaces. arXiv, abs/1908.02013, 1-9. 2019 Maicas, G., Bradley, A. P., Nascimento, J. C., Reid, I., & Carneiro, G. (2019). Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI. Medical Image Analysis, 58, 101562-1-101562-14.
Scopus26 WoS16 Europe PMC52019 Felix, R., Sasdelli, M., Reid, I. D., & Carneiro, G. (2019). Multi-modal Ensemble Classification for Generalized Zero Shot Learning.. CoRR, abs/1901.04623. 2019 Carneiro, G., Manuel, J., Tavares, R. S., Bradley, A. P., Papa, J. P., Nascimento, J. C., . . . Belagiannis, V. (2019). Editorial. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 7(3), 241.
Scopus1 WoS12019 Liu, Y., Tian, Y., Maicas, G., Pu, L. Z. C. T., Singh, R., Verjans, J. W., & Carneiro, G. (2019). Photoshopping Colonoscopy Video Frames.. CoRR, abs/1910.10345. 2019 Glaser, S., Maicas, G., Bedrikovetski, S., Sammour, T., & Carneiro, G. (2019). Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT.. CoRR, abs/1910.10371. 2019 Felix, R., Harwood, B., Sasdelli, M., & Carneiro, G. (2019). Generalised Zero-Shot Learning with Domain Classification in a Joint Semantic and Visual Space.. CoRR, abs/1908.04930. 2019 Sünderhauf, N., Dayoub, F., Hall, D., Skinner, J., Zhang, H., Carneiro, G., & Corke, P. (2019). A probabilistic challenge for object detection. Nature Machine Intelligence, 1(9), 443.
WoS12018 Snaauw, G., Gong, D., Maicas, G., Hengel, A. V. D., Niessen, W. J., Verjans, J., & Carneiro, G. (2018). End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging.. CoRR, abs/1810.10117. 2018 Gale, W., Oakden-Rayner, L., Carneiro, G., Bradley, A. P., & Palmer, L. J. (2018). Producing radiologist-quality reports for interpretable artificial intelligence.. CoRR, abs/1806.00340. 2018 Carneiro, G., Tavares, J. M. R. S., Bradley, A. P., Papa, J. P., Nascimento, J. C., Cardoso, J. S., . . . Belagiannis, V. (2018). 1st MICCAI workshop on deep learning in medical image analysis. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 6(3), 241-242.
2017 Dhungel, N., Carneiro, G., & Bradley, A. (2017). A deep learning approach for the analysis of masses in mammograms with minimal user intervention. Medical Image Analysis, 37, 114-128.
Scopus299 WoS196 Europe PMC722017 Gale, W., Oakden-Rayner, L., Carneiro, G., Bradley, A. P., & Palmer, L. J. (2017). Detecting hip fractures with radiologist-level performance using deep neural networks.. CoRR, abs/1711.06504. 2017 Carneiro, G., Nascimento, J., & Bradley, A. (2017). Automated analysis of unregistered multi-view mammograms with deep learning. IEEE Transactions on Medical Imaging, 36(11), 2355-2365.
Scopus166 WoS101 Europe PMC282017 Nascimento, J., & Carneiro, G. (2017). Deep learning on sparse manifolds for faster object segmentation. IEEE Transactions on Image Processing, 26(10), 4978-4990.
Scopus14 WoS14 Europe PMC32017 Ngo, T. A., Lu, Z., & Carneiro, G. (2017). Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance. Medical Image Analysis, 35, 159-171.
Scopus291 WoS231 Europe PMC862017 Lu, Z., Carneiro, G., Bradley, A., Ushizima, D., Nosrati, M., Bianchi, A., . . . Hamarneh, G. (2017). Evaluation of three algorithms for the segmentation of overlapping cervical cells. IEEE Journal of Biomedical and Health Informatics, 21(2), 441-450.
Scopus121 WoS74 Europe PMC302017 Ribeiro, D., Nascimento, J., Bernardino, A., & Carneiro, G. (2017). Improving the performance of pedestrian detectors using convolutional learning. Pattern Recognition, 61, 641-649.
Scopus33 WoS272017 Oakden-Rayner, L., Carneiro, G., Bessen, T., Nascimento, J., Bradley, A., & Palmer, L. (2017). Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework. Scientific Reports, 7(1), 13 pages.
Scopus121 WoS96 Europe PMC632017 Liao, Z., & Carneiro, G. (2017). A deep convolutional neural network module that promotes competition of multiple-size filters. Pattern Recognition, 71, 94-105.
Scopus24 WoS212017 Carneiro, G., Peng, T., Bayer, C., & Navab, N. (2017). Automatic quantification of tumour hypoxia from multi-modal microscopy images using weakly-supervised learning methods. IEEE Transactions on Medical Imaging, 36(7), 1405-1417.
Scopus4 WoS4 Europe PMC22017 Griffits, S., Hines, S., Moloney, C., & Ralph, N. (2017). Characteristics and processes of clinical reasoning in nurses and factors related to its use: a scoping review protocol. JBI database of systematic reviews and implementation reports, 15(12), 2832-2836.
Scopus10 Europe PMC52016 Lu, Z., Carneiro, G., Dhungel, N., & Bradley, A. P. (2016). Automated Detection of Individual Micro-calcifications from Mammograms
using a Multi-stage Cascade Approach.2015 Vochin, M., Borcoci, E., & Carneiro, G. (2015). Media aware network element data plane performance evaluation. UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science, 77(3), 77-84. 2015 Lu, Z., Carneiro, G., & Bradley, A. (2015). An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells. IEEE Transactions on Image Processing, 24(4), 1261-1272.
Scopus217 WoS155 Europe PMC412014 Iorga, R., Borcoci, E., Miruta, R., Pinto, A., Carneiro, G., & Calcada, T. (2014). Management driven hybrid multicast framework for content aware networks. IEEE Communications Magazine, 52(1), 158-165.
Scopus1 WoS12013 Carneiro, G., & Nascimento, J. (2013). Combining Multiple Dynamic Models and Deep Learning Architectures for Tracking the Left Ventricle Endocardium in Ultrasound Data.. IEEE transactions on pattern analysis and machine intelligence. 2013 Carneiro, G., & Nascimento, J. (2013). Combining multiple dynamic models and deep learning architectures for tracking the left ventricle endocardium in ultrasound data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(11), 2592-2607.
Scopus119 WoS90 Europe PMC332013 Carneiro, G. (2013). Artistic image analysis using graph-based learning approaches. IEEE Transactions on Image Processing, 22(8), 3168-3178.
Scopus5 WoS42012 Carneiro, G., Nascimento, J., & Freitas, A. (2012). The segmentation of the left ventricle of the heart from ultrasound data using deep learning architectures and derivative-based search methods. IEEE Transactions on Image Processing, 21(3), 968-982.
Scopus183 WoS150 Europe PMC472012 Carneiro, G., Fortuna, P., Dias, J., & Ricardo, M. (2012). Transparent and scalable terminal mobility for vehicular networks. Computer Networks, 56(2), 577-597.
Scopus2 WoS12012 Del Monego, H., Carneiro, G., Oliveira, J. M., & Ricardo, M. (2012). An ns-3 architecture for simulating joint radio resource management strategies in interconnected WLAN and UMTS networks. Transactions on emerging telecommunications technologies, 23(6), 537-549.
Scopus1 WoS12011 Carneiro, G., Fontes, H., & Ricardo, M. (2011). Fast prototyping of network protocols through ns-3 simulation model reuse. Simulation Modelling Practice and Theory, 19(9), 2063-2075.
Scopus21 WoS122009 Wels, M., Zheng, Y., Carneiro, G., Huber, M., Hornegger, J., & Comaniciu, D. (2009). Fast and robust 3-D MRI brain structure segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5762 LNCS(PART 2), 575-583.
Scopus19 Europe PMC62009 Carneiro, G., & Vasconcelos, N. (2009). Minimum Bayes error features for visual recognition. Image and Vision Computing, 27(1-2), 131-140.
Scopus2 WoS22009 Carneiro, G., & Jepson, A. (2009). The quantitative characterization of the distinctiveness and robustness of local image descriptors. Image and Vision Computing, 27(8), 1143-1156.
Scopus11 WoS102009 Zalud, I., Good, S., Carneiro, G., Georgescu, B., Aoki, K., Green, L., . . . Okumura, R. (2009). Fetal biometry: a comparison between experienced sonographers and automated measurements. The Journal of Maternal - Fetal & Neonatal Medicine, 22(1), 43-50.
Scopus15 WoS15 Europe PMC62008 Carneiro, G., Georgescu, B., Good, S., & Comaniciu, D. (2008). Detection and measurement of fetal anatomies from ultrasound images using a constrained probabilistic boosting tree. IEEE Transactions on Medical Imaging, 27(9), 1342-1355.
Scopus180 WoS139 Europe PMC542008 Wels, M., Carneiro, G., Aplas, A., Huber, M., Hornegger, J., & Comaniciu, D. (2008). A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5241 LNCS(PART 1), 67-75.
Scopus70 WoS45 Europe PMC192007 Carneiro, G., Georgescu, B., Good, S., & Comaniciu, D. (2007). Automatic fetal measurements in ultrasound using constrained probabilistic boosting tree. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4792 LNCS(PART 2), 571-579.
Scopus21 Europe PMC42007 Carneiro, G., & Ricardo, M. (2007). QoS abstraction layer in 4G access networks. Telecommunication Systems, 35(1-2), 55-65.
Scopus2 WoS12007 Carneiro, G., & Jepson, A. (2007). Flexible spatial configuration of local image features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(12), 2089-2104.
Scopus50 WoS34 Europe PMC52007 Carneiro, G., Chan, A., Moreno, P., & Vasconcelos, N. (2007). Supervised learning of semantic classes for image annotation and retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(3), 394-410.
Scopus791 WoS520 Europe PMC402004 Carneiro, G., Ruela, J., & Ricardo, M. (2004). Cross-layer design in 4G wireless terminals. IEEE Wireless Communications, 11(2), 7-13.
Scopus134 WoS741999 Aude, E. P. L., Carneiro, G. H. M. B., Serdeira, H., Silveira, J. T. C., Martins, M. F., & Lopes, E. P. (1999). CONTROLAB MUFA: a multi-level fusion architecture for intelligent navigation of a telerobot. Proceedings - IEEE International Conference on Robotics and Automation, 1, 465-472.
Scopus12 WoS11- Dalva, M., Van Leeuwen Bichara, G. C., Campos Cunha Filho, C. E., Carneiro, G. F., Saliba, G. N., Camacho, J. A., . . . Limaco, R. P. (n.d.). Intermittent annular reduction with Alfieri's repair in the treatment of mitral insufficiency in children: initial results. REVISTA BRASILEIRA DE CIRURGIA CARDIOVASCULAR, 24(3), 354-358.
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Books
Year Citation 2024 Carneiro, G. (2024). Machine Learning With Noisy Labels. Elsevier.
DOI2021 Rosen-Zvi, M., Gabrani, M., Konukoglu, E., Beymer, D., Carneiro, G., & Guindy, M. (2021). LL-COVID-19 preface (Vol. 12969 LNCS). 2020 Garg, S., Sünderhauf, N., Dayoub, F., Morrison, D., Cosgun, A., Carneiro, G., . . . Milford, M. (2020). Semantics for Robotic Mapping, Perception and Interaction: A Survey (Vol. 8). United States: Now Publishers.
DOI2019 Carneiro, G., & You, S. (2019). Computer Vision – ACCV 2018 Workshops (Vol. 11367 LNCS). G. Carneiro, & S. You (Eds.), Springer. 2019 Carneiro, G., & You, S. (2019). Computer Vision – ACCV 2018 Workshops (Vol. 11367 LNCS). G. Carneiro, & S. You (Eds.), Springer. 2019 Lu, L., Wang, X., Carneiro, G., & Yang, L. (2019). Preface. 2016 Carneiro, G., Tavares, J. M. R. S., Bradley, A., Papa, J. P., Nascimento, J. C., Cardoso, J. S., . . . Lu, Z. (2016). Preface: DLMIA 2016 (Vol. 10008 LNCS). 2016 Mateus, D., Peter, L., Carneiro, G., Loog, M., & Cornebise, J. (2016). Preface: LABELS 2016 (Vol. 10008 LNCS). 2016 Carneiro, G., Mateus, D., Peter, L., Bradley, A., Tavares, J. M. R. S., Belagiannis, V., . . . Cornebise, J. (Eds.) (2016). Deep Learning and Data Labeling for Medical Applications. Springer International Publishing.
DOI2016 Carneiro, G., Mateus, D., Peter, L., Bradley, A., Tavares, J. M. R. S., Belagiannis, V., . . . Cornebise, J. (Eds.) (2016). Deep Learning and Data Labeling for Medical Applications. Springer International Publishing.
DOI- Barclay, K., & Richardson, S. (Eds.) (n.d.). Performing the Self. Routledge.
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Book Chapters
Year Citation 2023 Amatriain, X., Balaji, Y., Bekiranov, S., Belagiannis, V., Benyoussef, A. -A., Carneiro, G., . . . Zhou, J. (2023). Contributors. In Meta Learning With Medical Imaging and Health Informatics Applications (pp. xv-xix). Elsevier.
DOI2023 Nguyen, C. C., Dawoud, Y., Do, T. -T., Nascimento, J. C., Belagiannis, V., & Carneiro, G. (2023). Smart task design for meta learning medical image analysis systems. In H. V. Nguyen, R. Summers, & R. Chellappa (Eds.), Meta Learning With Medical Imaging and Health Informatics Applications (pp. 185-209). Elsevier.
DOI2022 Nguyen, C., Dawoud, Y., Do, T. -T., Nascimento, J., Belagiannis, V., & Carneiro, G. (2022). Smart task design for meta learning medical image analysis systems: Unsupervised, weakly-supervised, and cross-domain design of meta learning tasks. In H. V. Nguyen, R. Summers, & R. Chellappa (Eds.), Meta-Learning with Medical Imaging and Health Informatics Applications (pp. 185-209). Elsevier.
DOI Scopus12022 Mehta, O., Liao, Z., Jenkinson, M., Carneiro, G., & Verjans, J. (2022). Machine Learning in Medical Imaging - Clinical Applications and Challenges in Computer Vision. In Artificial Intelligence in Medicine: Applications, Limitations and Future Directions (pp. 79-99). Springer Nature Singapore.
DOI Scopus32019 Verjans, J., Veldhuis, W. B., Carneiro, G., Wolterink, J. M., Išgum, I., & Leiner, T. (2019). Cardiovascular diseases. In E. R. Ranschaert, S. Morozov, & P. R. Algra (Eds.), Artificial Intelligence in Medical Imaging: Opportunities, Applications and Risks (pp. 167-185). Cham, Switzerland: Springer.
DOI Scopus32019 Maicas, G., Bradley, A. P., Nascimento, J. C., Reid, I., & Carneiro, G. (2019). Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI. In L. Lu, X. Wang, G. Carneiro, & L. Yang (Eds.), Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics (pp. 163-178). Cham, Switzerland: Springer.
DOI Scopus12019 Maicas, G., Bradley, A. P., Nascimento, J. C., Reid, I., & Carneiro, G. (2019). Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI. In L. Lu, X. Wang, G. Carneiro, & L. Yang (Eds.), Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics (pp. 163-178). Cham, Switzerland: Springer.
DOI Scopus12019 Carneiro, G., & You, S. (2019). Preface. In G. Carneiro, & S. You (Eds.), Computer Vision – ACCV 2018 Workshops (Vol. 11367 LNCS, pp. v). 2019 Carneiro, G., & You, S. (2019). Preface. In G. Carneiro, & S. You (Eds.), Computer Vision – ACCV 2018 Workshops (Vol. 11367 LNCS, pp. v). 2018 Carneiro, G., Tavares, J., Bradley, A., Papa, J., Belagiannis, V., Nascimento, J., . . . Conjeti, S. (2018). DLMIA 2018 Preface. In D. Stoyanov, Z. Taylor, G. Carneiro, & T. Syeda-Mahmood (Eds.), Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018 and 8th International Workshop, ML-CDS 2018 Held in Conjunction with MICCAI 2018 Granada, Spain, September 20, 2018 Proceedings (Vol. 11045 LNCS, pp. VII). 2018 Carneiro, G., Tavares, J., Bradley, A., Papa, J., Belagiannis, V., Nascimento, J., . . . Conjeti, S. (2018). DLMIA 2018 Preface. In D. Stoyanov, Z. Taylor, G. Carneiro, & T. Syeda-Mahmood (Eds.), Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018 and 8th International Workshop, ML-CDS 2018 Held in Conjunction with MICCAI 2018 Granada, Spain, September 20, 2018 Proceedings (Vol. 11045 LNCS, pp. VII). 2017 Carneiro, G., Nascimento, J., & Bradley, A. (2017). Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions. In S. Zhou, H. Greenspan, & D. Shen (Eds.), Deep Learning for Medical Image Analysis (pp. 321-339). London: Elsevier.
DOI Scopus342017 Carneiro, G., Zheng, Y., Xing, F., & Yang, L. (2017). Review of deep learning methods in mammography, cardiovascular, and microscopy image analysis. In L. Lu, Y. Zheng, G. Carneiro, & L. Yang (Eds.), Deep Learning and Convolutional Neural Networks for Medical Image Computing: precision medicine, high performance and large-scale datasets (pp. 11-32). Switzerland: Springer.
DOI Scopus422017 Ngo, T., & Carneiro, G. (2017). Fully automated segmentation using distance regularised level set and deep-structured learning and inference. In L. Lu, Y. Zheng, G. Carneiro, & L. Yang (Eds.), Deep Learning and Convolutional Neural Networks for Medical Image Computing: precision medicine, high performance and large-scale datasets (pp. 197-224). Switzerland: Springer.
DOI Scopus52017 Dhungel, N., Carneiro, G., & Bradley, A. (2017). Combining deep learning and structured prediction for segmenting masses in mammograms. In L. Lu, Y. Zheng, G. Carneiro, & L. Yang (Eds.), Deep Learning and Convolutional Neural Networks for Medical Image Computing: precision medicine, high performance and large-scale datasets (pp. 225-240). Switzerland: Springer.
DOI Scopus92016 Nascimento, J., Carneiro, G., & Freitas, A. (2016). Tracking and segmentation of the endocardium of the left ventricle in a 2D ultrasound using deep learning architectures and monte carlo sampling. In A. El-Baz, X. Jiang, & J. S. Suri (Eds.), Biomedical Image Segmentation: Advances and Trends (pp. 387-406). Florida; USA: CRC Press.
DOI Scopus22015 Chen, Q., & Carneiro, G. (2015). Artistic Image Analysis Using the Composition of Human Figures. In Lecture Notes in Computer Science (pp. 117-132). Springer International Publishing.
DOI2004 Thomas, N. N. M., Rea, G. L., & Weinstein, P. R. (2004). Anatomy and Pathophysiology of Acquired Spinal Lesions. In Spine Surgery: Techniques, Complication Avoidance, and Management, 2-Volume Set (pp. 88-99). Elsevier.
DOI Scopus1 -
Conference Papers
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Conference Items
Year Citation 2023 Tan, J. L., Pitawela, D., Chinnaratha, A., Chen, H. -T., Carneiro, G., & Singh, R. (2023). Enhancing accuracy in Barrett's surveillance using artificial intelligence: A multimodal (white-light and narrow-band imaging) model comparing vision transformer and convolutional neural networks. Poster session presented at the meeting of Abstracts of the Gastroenterological Society of Australia (GESA) Australian Gastroenterology Week (AGW) 2023, as published in Journal of gastroenterology and hepatology. Brisbane: Wiley.
DOI2017 Carneiro, G., Oakden-Rayner, L., Bradley, A. P., Nascimento, J. C., & Palmer, L. J. (2017). Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography.. Poster session presented at the meeting of ISBI. IEEE. 2017 Carneiro, G., Tavares, J., Bradley, A., Papa, J., Nascimento, J., Cardoso, J., . . . Lu, Z. (2017). Preface DLMIA 2017. Poster session presented at the meeting of Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017 Cheng, L. Z. T. P., Campbell, B., Carneiro, G., Burt, A. D., & Singh, R. (2017). Computer-aided diagnosis (CAD) for characterising colorectal lesions: Initial results of a newly developed software. Poster session presented at the meeting of JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY. WILEY. -
Patents
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Preprint
Year Citation 2024 Cordeiro, F., & Carneiro, G. (2024). Anne: Adaptive Nearest Neighbors and Eigenvector-Based Sample Selection for Robust Learning with Noisy Labels.
DOI2024 Al-qershi, O., Nguyen, T., Elliott, M., Schmidt, D., Makalic, E., Li, S., . . . Hopper, J. (2024). AutoCumulus: an Automated Mammographic Density Measure Created Using Artificial Intelligence.
DOI2024 Garg, A., Nguyen, C., Felix, R., Do, T. -T., & Carneiro, G. (2024). Pass: Peer-Agreement Based Sample Selection for Training with Instance-Dependent Noisy Labels.
DOI2024 Hopper, J., Nguyen, T. L., Elliott, M. S., Al-qershi, O., Schmidt, D. F., Makalic, E., . . . Frazer, H. (2024). Braix Risk Score: An Automated Mammogram-Based Biomarker for Breast Cancer Created by Applying Artificial Intelligence.
DOI2024 Masroor, M., Hassan, T., Tian, Y., Wells, K., Rosewarne, D., Do, T. -T., & Carneiro, G. (2024). Fair Distillation: Teaching Fairness from Biased Teachers in Medical
Imaging.2024 Garg, A., Nguyen, C., Felix, R., Do, T. -T., & Carneiro, G. (2024). Pass: Peer-Agreement Based Sample Selection for Training with Instance Dependent Noisy Labels.
DOI2024 Garg, A., Nguyen, C., Felix, R., Do, T. -T., & Carneiro, G. (2024). Pass: Peer-Agreement Based Sample Selection for Training with Instance Dependent Noisy Labels.
DOI2024 Sharma, Y., Mangoni, A. A., Mangoni, A., Horwood, C., & Thompson, C. (2024). Comparing Outcomes of Community-Acquired Pneumonia Patients Discharged from General Medicine and Respiratory Units in Australia: A Propensity Score-Matched Analysis.
DOI2023 Chen, Y., Liu, Y., Wang, C., Elliott, M., Kwok, C. F., Pena-Solorzano, C., . . . Carneiro, G. (2023). BRAIxDet: Learning to Detect Malignant Breast Lesion with Incomplete
Annotations.2023 Wang, C., Chen, Y., Liu, F., Liu, Y., McCarthy, D. J., Frazer, H., & Carneiro, G. (2023). Mixture of Gaussian-distributed Prototypes with Generative Modelling for
Interpretable and Trustworthy Image Recognition.2023 Galdran, A., Verjans, J., Carneiro, G., & Ballester, M. Á. G. (2023). Multi-Head Multi-Loss Model Calibration.. 2023 Wang, C., Liu, Y., Chen, Y., Liu, F., Tian, Y., McCarthy, D. J., . . . Carneiro, G. (2023). Learning Support and Trivial Prototypes for Interpretable Image
Classification.2022 Liu, Y., Tian, Y., Wang, C., Chen, Y., Liu, F., Belagiannis, V., & Carneiro, G. (2022). Translation Consistent Semi-supervised Segmentation for 3D Medical
Images.2022 Liu, Y., Ding, C., Tian, Y., Pang, G., Belagiannis, V., Reid, I., & Carneiro, G. (2022). Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection
in Semantic Segmentation.2022 Chen, Y., Liu, F., Wang, H., Wang, C., Tian, Y., Liu, Y., & Carneiro, G. (2022). BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray
Classification.2022 Tian, Y., Pang, G., Liu, Y., Wang, C., Chen, Y., Liu, F., . . . Carneiro, G. (2022). Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder.. 2021 Tian, Y., Pu, L. Z. C. T., Liu, Y., Maicas, G., Verjans, J. W., Burt, A. D., . . . Carneiro, G. (2021). Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning..
Centre of Excellence for Robotic Vision (ARC CoE 2014-2020)
Indo-Australian Biotechnology Fund (IABF) Project: New class of intelligent robotic imaging system for keyhole surgeries (2017-2020)
Discovery Project: Automated Analysis of Multi-modal Medical Data using Deep Belief Networks (ARC Discovery Project 2014-2016)
Linkage Infrastructure, Equipment and Facilities Project: Computational infrastructure for developing deep machine learning models (ARC LIEF 2016)
University of Adelaide - Interdisciplinary Research Fund Grant – Project Title: Novel Applications of Machine Learning in Healthcare (2016-2017).
Automatic Quantification of Acute and Chronic Hypoxia in Tumors from Immunohistochemical Fluorescence Images using Deep Structured Inference (Humboldt Fellowship 2014-2015)
Combining Multiple Dynamic Models and Deep Learning Architectures for Tracking the Left Ventricle Endocardium in Ultrasound Data (Portuguese Science Foundation FCT 2010-2012)
Printart: Where Computer Vision Meets Art (Portuguese Science Foundation FCT 2010-2012)
Learning to Combine Hierarchical Image Modeling with 2-D Segmentation and 3-D Pose Recovery of Visual Objects (Marie Curie International Incoming Fellowship 2010-2011)
University of Adelaide
- Puzzle-Based Learning (Fall 2017)
- Computer Graphics (Fall 2017)
- Topics in Computer Science (Fall 2017)
- Advanced Topics in Computer Science (Fall 2017)
- Puzzle-Based Learning (Fall 2016)
- Topics in Computer Science (Fall 2016)
- Object Oriented Programming (Spring 2015)
- Topics in Computer Science (Spring 2015)
- Computer Graphics (Fall 2015) - Videos of Best Projects
- Puzzle-Based Learning (Fall 2015)
- Topics in Computer Science (Fall 2015)
- Puzzle-Based Learning (Fall 2014)
- Software Engineering in Industry (Fall 2014)
- Topics in Computer Science (Fall 2014)
- Puzzle-Based Learning (Spring 2013)
- Software Engineering Group Project 1B (Spring 2013)
- Master of Software Engineering Project (Spring 2013)
- Computer Graphics (Fall 2013) - Videos of Best Projects
- Puzzle-Based Learning (Fall 2013)
- Puzzle-Based Learning (Spring 2012)
- Computer Vision (Fall 2012)
- Computer Graphics (Fall 2012) - Videos of Best Projects
Instituto Superior Tecnico - University of Lisbon
- Signals and Systems (Fall 2009)
- Robotics (Spring 2009)
- Modeling and Simulation (Spring 2009)
- Signal Processing (Fall 2008)
- Control (Fall 2008)
University of Toronto
- CSC 324 - Principles of Programming Languages (Fall 2004)
- CSC 446, Computer Methods for Partial Differential Equations (TA) (Winter 2002).
- CSC 418, Computer Graphics (TA) (1999-2003).
- CSC 458, Computer Networks (TA) (Winter 2000).
- CSC 258, Computer Organization (TA) (Summer 2000).
- CSC 260, An Introduction to Scientific, Symbolic, and Graphical Computation (TA) (Winter 2003).
- SCI 199, Computer and Images. (TA) (2000-2001)
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2023 Co-Supervisor Artificial Intelligence and Endoscopy - Enhancing early detection and improving outcomes in dysplasia and cancer of the Upper Gastrointestinal Tracts. Doctor of Philosophy Doctorate Full Time Mr Jin Lin Tan 2023 Co-Supervisor Enhancing Medical Decision-Making with Reinforcement Learning Master of Philosophy Master Full Time Mr Nilesh Ramgolam 2022 Co-Supervisor Improving Colorectal cancer detection through Colonoscopy exams with Explainable AI and Teachable AI Doctor of Philosophy Doctorate Full Time Mr Dileepa Pitawela 2021 Principal Supervisor Learning noisy labels using causal approaches Doctor of Philosophy Doctorate Full Time Mr Arpit Garg 2020 Co-Supervisor Computer Vision and Machine Learning for Navigation and Planning Doctor of Philosophy Doctorate Full Time Mr Sam Bahrami -
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2021 - 2024 Principal Supervisor Exploiting Correspondences in Multi-perspective Data Learning Doctor of Philosophy Doctorate Full Time Mr Yuanhong Chen 2021 - 2024 Principal Supervisor Interpretable Deep Learning for Medical Imaging and Computer Vision Doctor of Philosophy Doctorate Full Time Mr Chong Wang 2021 - 2023 Principal Supervisor The Utility of Validation Sets for Meta-learning Methods for Noisy-Label and Imbalanced Learning Problems Master of Philosophy Master Full Time Mr Dung Anh Hoang 2021 - 2021 Principal Supervisor Relaxed Invariant Representation for Unsupervised Domain Adaptation Master of Philosophy Master Full Time Mr Hossein Askari Lyarjdameh 2021 - 2025 Principal Supervisor Unpaired Multi-modal Multi-label Classification for Endometriosis Signs Doctor of Philosophy Doctorate Full Time Ms Yuan Zhang 2020 - 2024 Principal Supervisor Weakly-supervised learning in Computer Vision and Medical Imaging Doctor of Philosophy Doctorate Full Time Mr Fengbei Liu 2020 - 2024 Principal Supervisor Label Efficient Learning for Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Yuyuan Liu 2019 - 2019 Principal Supervisor Efficient Deep Learning Models with Autoencoder Regularization and Information Bottleneck Compression Master of Philosophy Master Full Time Mr Jerome Oskar Williams 2019 - 2022 Principal Supervisor Anomaly Detection in Computer Vision and Medical Imaging Doctor of Philosophy Doctorate Full Time Mr Yu Tian 2018 - 2022 Principal Supervisor Harnessing meta-learning via probabilistic modelling and trajectory optimisation Doctor of Philosophy Doctorate Full Time Mr Cuong Cao Nguyen 2018 - 2022 Principal Supervisor Weakly Supervised Localisation for Censor Aware Survival Prediction from Medical Images Doctor of Philosophy Doctorate Full Time Mr Renato Hermoza Aragones 2017 - 2020 Co-Supervisor Endoscopy-Focused Primary, Secondary and Tertiary Prevention of Colorectal Cancer Doctor of Philosophy under a Jointly-awarded Degree Agreement with Doctorate Full Time Dr Leonardo Zorron Cheng Tao Pu 2017 - 2020 Co-Supervisor Self-Supervised Learning for Geometry Doctor of Philosophy Doctorate Full Time Mr Huangying Zhan 2016 - 2022 Co-Supervisor Closing the implementation gap in pre-deployment medical AI study design Doctor of Philosophy Doctorate Part Time Dr Lauren Oakden-Rayner 2016 - 2020 Principal Supervisor Bayesian Data Augmentation and Generative Active Learning for Robust Imbalanced Deep Learning Doctor of Philosophy Doctorate Full Time Mr Toan Minh Tran 2016 - 2020 Principal Supervisor Data Augmentation for Multi-domain and Multi-model Generalised Zero-shot Learning Doctor of Philosophy Doctorate Full Time Dr Rafael Felix Alves 2015 - 2018 Principal Supervisor Pre-hoc and Post-hoc Diagnosis and Interpretation of Breast Magnetic Resonance Volumes Doctor of Philosophy Doctorate Full Time Mr Gabriel Maicas Suso 2015 - 2020 Principal Supervisor Single View 3D Reconstruction using Deep Learning Doctor of Philosophy Doctorate Part Time Adrian Robert Johnston 2013 - 2017 Principal Supervisor Methods for Understanding and Improving Deep Learning Classification Models Doctor of Philosophy Doctorate Full Time Dr Zhibin Liao 2013 - 2017 Co-Supervisor Moving Least Squares Registration in Computer Vision: New Applications and Algorithms Doctor of Philosophy Doctorate Full Time Mr Xiang Liu 2013 - 2016 Principal Supervisor Automated Detection, Segmentation and Classification of Masses from Mammograms using Deep Learning Doctor of Philosophy Doctorate Full Time Mr Neeraj Dhungel 2011 - 2016 Principal Supervisor Medical Image Segmentation Combining Level Set Method and Deep Belief Networks Doctor of Philosophy Doctorate Full Time Mr Tuan Anh Ngo
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