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Books and Theses
- 1996
[b1]Andrew P. Bradley
:
Machine learning for medical diagnostics: techniques for feature extraction, classification, and evaluation. University of Queensland, Australia, 1996
Journal Articles
- 2022
- [j24]Filip Rusak, Rodrigo Santa Cruz, Léo Lebrat, Ondrej Hlinka, Jurgen Fripp, Elliot Smith, Clinton Fookes, Andrew P. Bradley, Pierrick Bourgeat:
Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods. Medical Image Anal. 82: 102576 (2022) - 2020
- [j23]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu:
Special issue: 4th MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 501 (2020) - 2019
- [j22]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis:
Editorial. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 7(3): 241 (2019) - [j21]Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro:
Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI. Medical Image Anal. 58 (2019) - 2018
- [j20]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis:
1st MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 6(3): 241-242 (2018) - 2017
- [j19]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
A deep learning approach for the analysis of masses in mammograms with minimal user intervention. Medical Image Anal. 37: 114-128 (2017) - [j18]Zhi Lu, Gustavo Carneiro, Andrew P. Bradley, Daniela Ushizima, Masoud S. Nosrati, Andrea G. C. Bianchi, Cláudia M. Carneiro, Ghassan Hamarneh:
Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells. IEEE J. Biomed. Health Informatics 21(2): 441-450 (2017) - [j17]Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley:
Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning. IEEE Trans. Medical Imaging 36(11): 2355-2365 (2017) - 2015
- [j16]Zhi Lu, Gustavo Carneiro, Andrew P. Bradley:
An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells. IEEE Trans. Image Process. 24(4): 1261-1272 (2015) - 2014
- [j15]Andrew P. Bradley:
Half-AUC for the evaluation of sensitive or specific classifiers. Pattern Recognit. Lett. 38: 93-98 (2014) - 2013
- [j14]Michael Charles Stevens, Andrew P. Bradley, Stephen J. Wilson, David G. Mason:
Evaluation of a morphological filter in mean cardiac output determination: application to left ventricular assist devices. Medical Biol. Eng. Comput. 51(8): 891-899 (2013) - [j13]Andrew P. Bradley:
ROC curve equivalence using the Kolmogorov-Smirnov test. Pattern Recognit. Lett. 34(5): 470-475 (2013) - 2010
- [j12]Nahla H. Barakat, Andrew P. Bradley:
Rule extraction from support vector machines: A review. Neurocomputing 74(1-3): 178-190 (2010) - [j11]Noor Azah Samsudin, Andrew P. Bradley:
Nearest neighbour group-based classification. Pattern Recognit. 43(10): 3458-3467 (2010) - [j10]Nahla H. Barakat, Andrew P. Bradley, Mohamed Nabil H. Barakat:
Intelligible support vector machines for diagnosis of diabetes mellitus. IEEE Trans. Inf. Technol. Biomed. 14(4): 1114-1120 (2010) - [j9]Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Dominic Kennedy, Stuart Crozier:
Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means. IEEE Trans. Medical Imaging 29(2): 302-310 (2010) - 2007
- [j8]Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson, John Williams, Peter J. Kootsookos:
Correspondence-Free Determination of the Affine Fundamental Matrix. IEEE Trans. Pattern Anal. Mach. Intell. 29(1): 82-97 (2007) - [j7]Nahla H. Barakat, Andrew P. Bradley:
Rule Extraction from Support Vector Machines: A Sequential Covering Approach. IEEE Trans. Knowl. Data Eng. 19(6): 729-741 (2007) - 2003
- [j6]Andrew P. Bradley, Fred Stentiford:
Visual attention for region of interest coding in JPEG 2000. J. Vis. Commun. Image Represent. 14(3): 232-250 (2003) - 1999
- [j5]Andrew P. Bradley:
A wavelet visible difference predictor. IEEE Trans. Image Process. 8(5): 717-730 (1999) - 1998
- [j4]Michael P. Eckert, Andrew P. Bradley:
Perceptual quality metrics applied to still image compression. Signal Process. 70(3): 177-200 (1998) - 1997
- [j3]Andrew P. Bradley:
The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit. 30(7): 1145-1159 (1997) - 1996
- [j2]Brian C. Lovell, Andrew P. Bradley:
The Multiscale Classifier. IEEE Trans. Pattern Anal. Mach. Intell. 18(2): 124-137 (1996) - [j1]Andrew P. Bradley:
ROC curves and the X2 test. Pattern Recognit. Lett. 17(3): 287-294 (1996)
Conference and Workshop Papers
- 2024
- [c60]Olivier Salvado, Salamata Konate, Rodrigo Santa Cruz, Andrew P. Bradley, Judy Wawira Gichoya, Laleh Seyyed-Kalantari, Brandon J. Price, Clinton Fookes, Léo Lebrat:
Localisation of Racial Information in Chest X-Ray for Deep Learning Diagnosis. ISBI 2024: 1-4 - 2023
- [c59]Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Andrew P. Bradley, Olivier Salvado:
Bias Identification with RankPix Saliency. ICASSP 2023: 1-5 - [c58]David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley:
Never mind the metrics - what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective. ICML 2023: 22702-22757 - [c57]Filip Rusak, Rodrigo Santa Cruz, Hilda Chourak, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley:
When to Use Augmentation - Variability Insufficient for Cortical Thickness Estimation Improvement. ISBI 2023: 1-5 - [c56]Margot Brereton, Aloha May Hufana Ambe, David R. Lovell, Laurianne Sitbon, Tara Capel, Alessandro Soro, Yue Xu, Catarina Moreira, Benoît Favre, Andrew P. Bradley:
Designing Interaction with AI for Human Learning: Towards Human-Machine Teaming in Radiology Training. OZCHI 2023: 639-647 - 2022
- [c55]Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley:
Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely. DALI@MICCAI 2022: 33-42 - 2021
- [c54]David Lovell, Bridget McCarron, Brendan Langfield, Khoa Tran, Andrew P. Bradley:
Taking the Confusion Out of Multinomial Confusion Matrices and Imbalanced Classes. AusDM 2021: 16-30 - [c53]Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Elliot Smith, Andrew P. Bradley, Clinton Fookes, Olivier Salvado:
A Comparison of Saliency Methods for Deep Learning Explainability. DICTA 2021: 1-8 - [c52]Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Andrew P. Bradley, Clinton Fookes, Olivier Salvado:
Smocam: Smooth Conditional Attention Mask For 3d-Regression Models. ISBI 2021: 362-366 - [c51]Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley:
Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation. SASHIMI@MICCAI 2021: 3-13 - 2020
- [c50]Hang Min, Devin Wilson, Yinhuang Huang, Siyu Liu, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra:
Fully Automatic Computer-aided Mass Detection and Segmentation via Pseudo-color Mammograms and Mask R-CNN. ISBI 2020: 1111-1115 - [c49]Filip Rusak, Rodrigo Santa Cruz, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Andrew P. Bradley, Olivier Salvado:
3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps. SASHIMI@MICCAI 2020: 11-20 - 2019
- [c48]Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian D. Reid, Gustavo Carneiro:
Model Agnostic Saliency For Weakly Supervised Lesion Detection From Breast DCE-MRI. ISBI 2019: 1057-1060 - [c47]William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley:
Producing Radiologist-Quality Reports for Interpretable Deep Learning. ISBI 2019: 1275-1279 - 2018
- [c46]Annika Reinke, Matthias Eisenmann, Sinan Onogur, Marko Stankovic, Patrick Scholz, Peter M. Full, Hrvoje Bogunovic, Bennett A. Landman, Oskar Maier, Bjoern H. Menze, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Fons van der Sommen, Guoyan Zheng, Henning Müller, Michal Kozubek, Tal Arbel, Andrew P. Bradley, Pierre Jannin, Annette Kopp-Schneider, Lena Maier-Hein:
How to Exploit Weaknesses in Biomedical Challenge Design and Organization. MICCAI (4) 2018: 388-395 - [c45]Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro:
Training Medical Image Analysis Systems like Radiologists. MICCAI (1) 2018: 546-554 - 2017
- [c44]Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features. ICIP 2017: 1737-1741 - [c43]Hang Min, Shekhar S. Chandra, Neeraj Dhungel, Stuart Crozier, Andrew P. Bradley:
Multi-scale mass segmentation for mammograms via cascaded random forests. ISBI 2017: 113-117 - [c42]Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto C. Nascimento, Lyle J. Palmer:
Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography. ISBI 2017: 130-134 - [c41]Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley:
Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior. ISBI 2017: 305-309 - [c40]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Fully automated classification of mammograms using deep residual neural networks. ISBI 2017: 310-314 - [c39]Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid:
Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI. MICCAI (3) 2017: 665-673 - 2016
- [c38]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. MICCAI (2) 2016: 106-114 - 2015
- [c37]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests. DICTA 2015: 1-8 - [c36]Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow:
Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels. DICTA 2015: 1-8 - [c35]Alex M. Pagnozzi, Nicholas D. H. Dowson, Andrew P. Bradley, Roslyn N. Boyd, Pierrick Bourgeat, Stephen E. Rose:
Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology. DICTA 2015: 1-6 - [c34]Kristian J. Weegink, John J. Varghese, Andrew P. Bradley:
Spikes from compound action potentials in simulated microelectrode recordings. ICASSP 2015: 813-816 - [c33]Fahira Afzal Maken, Andrew P. Bradley:
Multiple instance learning for breast MRI based on generic spatio-temporal features. ICASSP 2015: 902-906 - [c32]John J. Varghese, Kristian J. Weegink, P. A. Bellette, Andrew P. Bradley:
Spectral properties of neuronal pulse interval modulation. ICASSP 2015: 1007-1011 - [c31]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep structured learning for mass segmentation from mammograms. ICIP 2015: 2950-2954 - [c30]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms. ISBI 2015: 760-763 - [c29]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms. MICCAI (1) 2015: 605-612 - [c28]Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley:
Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models. MICCAI (3) 2015: 652-660 - [c27]Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow:
Segmentation of skin strata in reflectance confocal microscopy depth stacks. Image Processing 2015: 94131U - 2014
- [c26]Fahira A. Maken, Yaniv Gal, Darryl McClymont, Andrew P. Bradley:
Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging. DICTA 2014: 1-8 - [c25]Marnie L. Lamprecht, Philip Ian Terrill, Chloe L. Parsley, Andrew P. Bradley:
Characterization of movements during restless sleep in children: A pilot study. EMBC 2014: 274-277 - [c24]Yilun Fan, Yaniv Gal, Andrew P. Bradley:
Microscopic specimen delineation using auto-phase correlation index. ISBI 2014: 1336-1339 - [c23]Noor Azah Samsudin, Andrew P. Bradley:
Extended Naïve Bayes for Group Based Classification. SCDM 2014: 497-505 - 2013
- [c22]Doreen Altinay, Andrew P. Bradley:
Illumination Effects in Quantitative Virtual Microscopy. CAIP (2) 2013: 449-456 - [c21]Yilun Fan, Yaniv Gal, Andrew P. Bradley:
Performance Analysis of Three Microscope Slide Scanning Techniques. DICTA 2013: 1-6 - [c20]Kian B. Ng, Andrew P. Bradley, Ross Cunnington:
Effect of posterized naturalistic stimuli on SSVEP-based BCI. EMBC 2013: 3105-3108 - [c19]Zhi Lu, Gustavo Carneiro, Andrew P. Bradley:
Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells. MICCAI (1) 2013: 452-460 - 2012
- [c18]Steven D. Brossi, Andrew P. Bradley:
A Comparison of Multiple Instance and Group Based Learning. DICTA 2012: 1-8 - [c17]Kian B. Ng, Ross Cunnington, Andrew P. Bradley:
Enhancing the classification accuracy of Steady-State Visual Evoked Potential-based Brain-Computer Interface using Component Synchrony Measure. IJCNN 2012: 1-6 - 2011
- [c16]P. A. Meehan, P. A. Bellette, Andrew P. Bradley, J. E. Castner, Helen J. Chenery, David A. Copland, John J. Varghese, Terry Coyne, P. A. Silburn:
Investigation of the non-Markovity Spectrum as a Cognitive Processing Measure of Deep Brain Microelectrode Recordings. BIOSIGNALS 2011: 144-150 - [c15]Doreen Altinay, Andrew P. Bradley:
An Evaluation of Multi-resolution Microscope Slide Scanning Algorithms. DICTA 2011: 319-324 - [c14]Kian B. Ng, Andrew P. Bradley, Ross Cunnington:
Effect of competing stimuli on SSVEP-based BCI. EMBC 2011: 6307-6310 - 2010
- [c13]Doreen Altinay, Andrew P. Bradley, Andrew Mehnert:
On the Estimation of Extrinsic and Intrinsic Parameters of Optical Microscope Calibration. DICTA 2010: 190-195 - 2009
- [c12]Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Dominic Kennedy, Stuart Crozier:
Feature and Classifier Selection for Automatic Classification of Lesions in Dynamic Contrast-Enhanced MRI of the Breast. DICTA 2009: 132-139 - [c11]Nahla H. Barakat, Andrew P. Bradley:
The Effect of Domain Knowledge on Rule Extraction from Support Vector Machines. MLDM 2009: 311-321 - 2008
- [c10]Peter W. M. Ilbery, David Taubman, Andrew P. Bradley:
Mixed content image compression by gradient field integration. ICIP 2008: 1053-1056 - [c9]Noor Azah Samsudin, Andrew P. Bradley:
Group-based meta-classification. ICPR 2008: 1-4 - 2007
- [c8]Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Stuart Crozier:
Automatic Segmentation of Enhancing Breast Tissue in Dynamic Contrast-Enhanced MR Images. DICTA 2007: 124-129 - [c7]Jason Dowling, Birgit M. Planitz, Anthony J. Maeder, Jiang Du, Binh Pham, Colin Boyd, Shaokang Chen, Andrew P. Bradley, Stuart Crozier:
A Comparison of DCT and DWT Block Based Watermarking on Medical Image Quality. IWDW 2007: 454-466 - 2006
- [c6]Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson:
Estimation Of Epipolar Geometry Via The Radon Transform. ICASSP (2) 2006: 497-500 - [c5]Nahla H. Barakat, Andrew P. Bradley:
Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve. ICPR (2) 2006: 812-815 - 2005
- [c4]Andrew P. Bradley, Michael Wildermoth, Paul Mills:
Virtual Microscopy with Extended Depth of Field. DICTA 2005: 35 - [c3]Ben Appleton, Andrew P. Bradley, Michael Wildermoth:
Towards Optimal Image Stitching for Virtual Microscopy. DICTA 2005: 44 - 2004
- [c2]Andrew P. Bradley, I. Dennis Longstaff:
Sample Size Estimation using the Receiver Operating Characteristic Curve. ICPR (4) 2004: 428-431 - 2003
- [c1]Andrew P. Bradley:
Shift-invariance in the Discrete Wavelet Transform. DICTA 2003: 29-38
Parts in Books or Collections
- 2019
- [p3]Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro:
Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics 2019: 163-178 - 2017
- [p2]Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley:
Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1. Deep Learning for Medical Image Analysis 2017: 321-339 - [p1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms. Deep Learning and Convolutional Neural Networks for Medical Image Computing 2017: 225-240
Editorship
- 2018
- [e5]Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne L. Martel, Lena Maier-Hein, Kanwal K. Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga:
Image Analysis for Moving Organ, Breast, and Thoracic Images - Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings. Lecture Notes in Computer Science 11040, Springer 2018, ISBN 978-3-030-00945-8 [contents] - [e4]Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, Anne L. Martel, Lena Maier-Hein, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, Anant Madabhushi:
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. Lecture Notes in Computer Science 11045, Springer 2018, ISBN 978-3-030-00888-8 [contents] - 2017
- [e3]M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, João Manuel R. S. Tavares, Mehdi Moradi, Andrew P. Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu:
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10553, Springer 2017, ISBN 978-3-319-67557-2 [contents] - 2016
- [e2]Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew P. Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise:
Deep Learning and Data Labeling for Medical Applications - First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Lecture Notes in Computer Science 10008, 2016, ISBN 978-3-319-46975-1 [contents] - 2011
- [e1]Andrew P. Bradley, Paul T. Jackway:
2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Noosa, QLD, Australia, December 6-8, 2011. IEEE Computer Society 2011, ISBN 978-1-4577-2006-2 [contents]
Informal and Other Publications
- 2022
- [i12]David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley:
Never mind the metrics - what about the uncertainty? Visualising confusion matrix metric distributions. CoRR abs/2206.02157 (2022) - 2020
- [i11]Hang Min, Darryl McClymont, Shekhar S. Chandra, Stuart Crozier, Andrew P. Bradley:
Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI. CoRR abs/2007.03199 (2020) - 2019
- [i10]Hang Min, Devin Wilson, Yinhuang Huang, Samuel Kelly, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra:
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN. CoRR abs/1906.12118 (2019) - 2018
- [i9]Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro:
Training Medical Image Analysis Systems like Radiologists. CoRR abs/1805.10884 (2018) - [i8]William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer:
Producing radiologist-quality reports for interpretable artificial intelligence. CoRR abs/1806.00340 (2018) - [i7]Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro J. Niessen, Nasir M. Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider:
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. CoRR abs/1806.02051 (2018) - [i6]Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian D. Reid, Gustavo Carneiro:
Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI. CoRR abs/1807.07784 (2018) - [i5]Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro:
Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI. CoRR abs/1809.09404 (2018) - 2017
- [i4]William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer:
Detecting hip fractures with radiologist-level performance using deep neural networks. CoRR abs/1711.06504 (2017) - 2016
- [i3]Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto C. Nascimento, Lyle J. Palmer:
Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography. CoRR abs/1607.00267 (2016) - [i2]Zhi Lu, Gustavo Carneiro, Neeraj Dhungel, Andrew P. Bradley:
Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach. CoRR abs/1610.02251 (2016) - 2014
- [i1]Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
Deep Structured learning for mass segmentation from Mammograms. CoRR abs/1410.7454 (2014)
Coauthor Index
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