Articles with public access mandates - Andrew P. BradleyLearn more
Available somewhere: 51
Deep learning in cancer diagnosis, prognosis and treatment selection
KA Tran, O Kondrashova, A Bradley, ED Williams, JV Pearson, N Waddell
Genome Medicine 13, 1-17, 2021
Mandates: National Health and Medical Research Council, Australia
A deep learning approach for the analysis of masses in mammograms with minimal user intervention
N Dhungel, G Carneiro, AP Bradley
Medical image analysis 37, 114-128, 2017
Mandates: Australian Research Council
Unregistered multiview mammogram analysis with pre-trained deep learning models
G Carneiro, J Nascimento, AP Bradley
International conference on medical image computing and computer-assisted …, 2015
Mandates: Australian Research Council
Why rankings of biomedical image analysis competitions should be interpreted with care
L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ...
Nature communications 9 (1), 5217, 2018
Mandates: Swiss National Science Foundation, US National Institutes of Health …
Automated mass detection in mammograms using cascaded deep learning and random forests
N Dhungel, G Carneiro, AP Bradley
2015 international conference on digital image computing: techniques and …, 2015
Mandates: Australian Research Council
An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells
Z Lu, G Carneiro, AP Bradley
IEEE transactions on image processing 24 (4), 1261-1272, 2015
Mandates: Australian Research Council
Automated analysis of unregistered multi-view mammograms with deep learning
G Carneiro, J Nascimento, AP Bradley
IEEE transactions on medical imaging 36 (11), 2355-2365, 2017
Mandates: Australian Research Council
Deep learning and structured prediction for the segmentation of mass in mammograms
N Dhungel, G Carneiro, AP Bradley
International Conference on Medical image computing and computer-assisted …, 2015
Mandates: Australian Research Council
Evaluation of three algorithms for the segmentation of overlapping cervical cells
Z Lu, G Carneiro, AP Bradley, D Ushizima, MS Nosrati, AGC Bianchi, ...
IEEE journal of biomedical and health informatics 21 (2), 441-450, 2016
Mandates: US Department of Energy, Australian Research Council, Natural Sciences and …
The automated learning of deep features for breast mass classification from mammograms
N Dhungel, G Carneiro, AP Bradley
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016
Mandates: Australian Research Council
Automated nucleus and cytoplasm segmentation of overlapping cervical cells
Z Lu, G Carneiro, AP Bradley
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013
Mandates: Australian Research Council
Deep reinforcement learning for active breast lesion detection from DCE-MRI
G Maicas, G Carneiro, AP Bradley, JC Nascimento, I Reid
International conference on medical image computing and computer-assisted …, 2017
Mandates: Australian Research Council
Fully automated classification of mammograms using deep residual neural networks
N Dhungel, G Carneiro, AP Bradley
2017 IEEE 14th International symposium on biomedical imaging (ISBI 2017 …, 2017
Mandates: Australian Research Council
Producing radiologist-quality reports for interpretable deep learning
W Gale, L Oakden-Rayner, G Carneiro, LJ Palmer, AP Bradley
2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019 …, 2019
Mandates: Australian Research Council
Deep structured learning for mass segmentation from mammograms
N Dhungel, G Carneiro, AP Bradley
2015 IEEE international conference on image processing (ICIP), 2950-2954, 2015
Mandates: Australian Research Council
Training medical image analysis systems like radiologists
G Maicas, AP Bradley, JC Nascimento, I Reid, G Carneiro
International Conference on Medical Image Computing and Computer-Assisted …, 2018
Mandates: Australian Research Council
Deep learning models for classifying mammogram exams containing unregistered multi-view images and segmentation maps of lesions
G Carneiro, J Nascimento, AP Bradley
Deep learning for medical image analysis, 321-339, 2017
Mandates: Australian Research Council
How to exploit weaknesses in biomedical challenge design and organization
A Reinke, M Eisenmann, S Onogur, M Stankovic, P Scholz, PM Full, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Mandates: European Commission
Tree re-weighted belief propagation using deep learning potentials for mass segmentation from mammograms
N Dhungel, G Carneiro, AP Bradley
2015 IEEE 12th international symposium on biomedical imaging (ISBI), 760-763, 2015
Mandates: Australian Research Council
Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior
G Maicas, G Carneiro, AP Bradley
2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017
Mandates: Australian Research Council
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