Andrew P. Bradley

105 papers A* 1B 6C 1Misc 21Journal 36Unranked 32

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Localisation of Racial Information in Chest X-Ray for Deep Learning Diagnosis. ISBI Olivier Salvado, Salamata Konate, Rodrigo Santa Cruz, Andrew P. Bradley, Judy Wawira Gichoya, Laleh Seyyed-Kalantari, Brandon J. Price, Clinton Fookes, Léo Lebrat
2023	Misc	`conf`	Bias Identification with RankPix Saliency. ICASSP Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Andrew P. Bradley, Olivier Salvado
2023	Misc	`conf`	Designing Interaction with AI for Human Learning: Towards Human-Machine Teaming in Radiology Training. OZCHI Margot Brereton, Aloha May Hufana Ambe, David R. Lovell, Laurianne Sitbon, Tara Capel, Alessandro Soro, Yue Xu, Catarina Moreira, Benoît Favre, Andrew P. Bradley
2023	A*	`conf`	Never mind the metrics - what about the uncertainty? Visualising binary confusion matrix metric distributions to put performance in perspective. ICML David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley
2023	—	`conf`	When to Use Augmentation - Variability Insufficient for Cortical Thickness Estimation Improvement. ISBI Filip Rusak, Rodrigo Santa Cruz, Hilda Chourak, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
2022	—	`conf`	Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely. DALI@MICCAI Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
2022	J	`jnl`	Never mind the metrics - what about the uncertainty? Visualising confusion matrix metric distributions. CoRR David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley
2022	J	`jnl`	Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods. Medical Image Anal. Filip Rusak, Rodrigo Santa Cruz, Léo Lebrat, Ondrej Hlinka, Jurgen Fripp, Elliot Smith, Clinton Fookes, Andrew P. Bradley, Pierrick Bourgeat
2021	Misc	`conf`	A Comparison of Saliency Methods for Deep Learning Explainability. DICTA Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Elliot Smith, Andrew P. Bradley, Clinton Fookes, Olivier Salvado
2021	—	`conf`	Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation. SASHIMI@MICCAI Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
2021	—	`conf`	Smocam: Smooth Conditional Attention Mask For 3d-Regression Models. ISBI Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Andrew P. Bradley, Clinton Fookes, Olivier Salvado
2021	Misc	`conf`	Taking the Confusion Out of Multinomial Confusion Matrices and Imbalanced Classes. AusDM David Lovell, Bridget McCarron, Brendan Langfield, Khoa Tran, Andrew P. Bradley
2020	—	`conf`	3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps. SASHIMI@MICCAI Filip Rusak, Rodrigo Santa Cruz, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Andrew P. Bradley, Olivier Salvado
2020	J	`jnl`	Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI. CoRR Hang Min, Darryl McClymont, Shekhar S. Chandra, Stuart Crozier, Andrew P. Bradley
2020	—	`conf`	Fully Automatic Computer-aided Mass Detection and Segmentation via Pseudo-color Mammograms and Mask R-CNN. ISBI Hang Min, Devin Wilson, Yinhuang Huang, Siyu Liu, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra
2020	J	`jnl`	Special issue: 4th MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu
2019	—	`ch.`	Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro
2019	J	`jnl`	Editorial. Comput. methods Biomech. Biomed. Eng. Imaging Vis. Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis
2019	J	`jnl`	Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN. CoRR Hang Min, Devin Wilson, Yinhuang Huang, Samuel Kelly, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra
2019	—	`conf`	Model Agnostic Saliency For Weakly Supervised Lesion Detection From Breast DCE-MRI. ISBI Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian D. Reid, Gustavo Carneiro
2019	J	`jnl`	Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI. Medical Image Anal. Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro
2019	—	`conf`	Producing Radiologist-Quality Reports for Interpretable Deep Learning. ISBI William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley
2018	J	`jnl`	1st MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis
2018	—	`ed.`	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 DLMIA/ML-CDS@MICCAI 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
2018	—	`conf`	How to Exploit Weaknesses in Biomedical Challenge Design and Organization. MICCAI (4) 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
2018	—	`ed.`	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 RAMBO+BIA+TIA@MICCAI 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
2018	J	`jnl`	Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. CoRR 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
2018	J	`jnl`	Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI. CoRR Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley, Ian D. Reid, Gustavo Carneiro
2018	J	`jnl`	Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI. CoRR Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro
2018	J	`jnl`	Producing radiologist-quality reports for interpretable artificial intelligence. CoRR William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer
2018	—	`conf`	Training Medical Image Analysis Systems like Radiologists. MICCAI (1) Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro
2018	J	`jnl`	Training Medical Image Analysis Systems like Radiologists. CoRR Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro
2017	J	`jnl`	A deep learning approach for the analysis of masses in mammograms with minimal user intervention. Medical Image Anal. Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2017	—	`conf`	Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography. ISBI Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto C. Nascimento, Lyle J. Palmer
2017	J	`jnl`	Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning. IEEE Trans. Medical Imaging Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley
2017	—	`ch.`	Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms. Deep Learning and Convolutional Neural Networks for Medical Image Computing Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2017	—	`ch.`	Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1. Deep Learning for Medical Image Analysis Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley
2017	—	`ed.`	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 DLMIA/ML-CDS@MICCAI 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
2017	—	`conf`	Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI. MICCAI (3) Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid
2017	J	`jnl`	Detecting hip fractures with radiologist-level performance using deep neural networks. CoRR William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer
2017	J	`jnl`	Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells. IEEE J. Biomed. Health Informatics Zhi Lu, Gustavo Carneiro, Andrew P. Bradley, Daniela Ushizima, Masoud S. Nosrati, Andrea G. C. Bianchi, Cláudia M. Carneiro, Ghassan Hamarneh
2017	—	`conf`	Fully automated classification of mammograms using deep residual neural networks. ISBI Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2017	—	`conf`	Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior. ISBI Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley
2017	B	`conf`	Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features. ICIP Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2017	—	`conf`	Multi-scale mass segmentation for mammograms via cascaded random forests. ISBI Hang Min, Shekhar S. Chandra, Neeraj Dhungel, Stuart Crozier, Andrew P. Bradley
2016	J	`jnl`	Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography. CoRR Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto C. Nascimento, Lyle J. Palmer
2016	J	`jnl`	Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach. CoRR Zhi Lu, Gustavo Carneiro, Neeraj Dhungel, Andrew P. Bradley
2016	—	`ed.`	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 LABELS/DLMIA@MICCAI 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
2016	—	`conf`	The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. MICCAI (2) Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2015	J	`jnl`	An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells. IEEE Trans. Image Process. Zhi Lu, Gustavo Carneiro, Andrew P. Bradley
2015	Misc	`conf`	Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels. DICTA Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow
2015	Misc	`conf`	Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests. DICTA Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2015	—	`conf`	Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms. MICCAI (1) Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2015	B	`conf`	Deep structured learning for mass segmentation from mammograms. ICIP Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2015	Misc	`conf`	Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology. DICTA Alex M. Pagnozzi, Nicholas D. H. Dowson, Andrew P. Bradley, Roslyn N. Boyd, Pierrick Bourgeat, Stephen E. Rose
2015	Misc	`conf`	Multiple instance learning for breast MRI based on generic spatio-temporal features. ICASSP Fahira Afzal Maken, Andrew P. Bradley
2015	B	`conf`	Segmentation of skin strata in reflectance confocal microscopy depth stacks. Image Processing Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow
2015	Misc	`conf`	Spectral properties of neuronal pulse interval modulation. ICASSP John J. Varghese, Kristian J. Weegink, P. A. Bellette, Andrew P. Bradley
2015	Misc	`conf`	Spikes from compound action potentials in simulated microelectrode recordings. ICASSP Kristian J. Weegink, John J. Varghese, Andrew P. Bradley
2015	—	`conf`	Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms. ISBI Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2015	—	`conf`	Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models. MICCAI (3) Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley
2014	—	`conf`	Characterization of movements during restless sleep in children: A pilot study. EMBC Marnie L. Lamprecht, Philip Ian Terrill, Chloe L. Parsley, Andrew P. Bradley
2014	J	`jnl`	Deep Structured learning for mass segmentation from Mammograms. CoRR Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
2014	—	`conf`	Extended Naïve Bayes for Group Based Classification. SCDM Noor Azah Samsudin, Andrew P. Bradley
2014	J	`jnl`	Half-AUC for the evaluation of sensitive or specific classifiers. Pattern Recognit. Lett. Andrew P. Bradley
2014	—	`conf`	Microscopic specimen delineation using auto-phase correlation index. ISBI Yilun Fan, Yaniv Gal, Andrew P. Bradley
2014	Misc	`conf`	Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging. DICTA Fahira A. Maken, Yaniv Gal, Darryl McClymont, Andrew P. Bradley
2013	—	`conf`	Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells. MICCAI (1) Zhi Lu, Gustavo Carneiro, Andrew P. Bradley
2013	—	`conf`	Effect of posterized naturalistic stimuli on SSVEP-based BCI. EMBC Kian B. Ng, Andrew P. Bradley, Ross Cunnington
2013	J	`jnl`	Evaluation of a morphological filter in mean cardiac output determination: application to left ventricular assist devices. Medical Biol. Eng. Comput. Michael Charles Stevens, Andrew P. Bradley, Stephen J. Wilson, David G. Mason
2013	—	`conf`	Illumination Effects in Quantitative Virtual Microscopy. CAIP (2) Doreen Altinay, Andrew P. Bradley
2013	Misc	`conf`	Performance Analysis of Three Microscope Slide Scanning Techniques. DICTA Yilun Fan, Yaniv Gal, Andrew P. Bradley
2013	J	`jnl`	ROC curve equivalence using the Kolmogorov-Smirnov test. Pattern Recognit. Lett. Andrew P. Bradley
2012	Misc	`conf`	A Comparison of Multiple Instance and Group Based Learning. DICTA Steven D. Brossi, Andrew P. Bradley
2012	B	`conf`	Enhancing the classification accuracy of Steady-State Visual Evoked Potential-based Brain-Computer Interface using Component Synchrony Measure. IJCNN Kian B. Ng, Ross Cunnington, Andrew P. Bradley
2011	Misc	`ed.`	2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Noosa, QLD, Australia, December 6-8, 2011 DICTA Andrew P. Bradley, Paul T. Jackway
2011	Misc	`conf`	An Evaluation of Multi-resolution Microscope Slide Scanning Algorithms. DICTA Doreen Altinay, Andrew P. Bradley
2011	—	`conf`	Effect of competing stimuli on SSVEP-based BCI. EMBC Kian B. Ng, Andrew P. Bradley, Ross Cunnington
2011	—	`conf`	Investigation of the non-Markovity Spectrum as a Cognitive Processing Measure of Deep Brain Microelectrode Recordings. BIOSIGNALS 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
2010	J	`jnl`	Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means. IEEE Trans. Medical Imaging Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Dominic Kennedy, Stuart Crozier
2010	J	`jnl`	Intelligible support vector machines for diagnosis of diabetes mellitus. IEEE Trans. Inf. Technol. Biomed. Nahla H. Barakat, Andrew P. Bradley, Mohamed Nabil H. Barakat
2010	J	`jnl`	Nearest neighbour group-based classification. Pattern Recognit. Noor Azah Samsudin, Andrew P. Bradley
2010	Misc	`conf`	On the Estimation of Extrinsic and Intrinsic Parameters of Optical Microscope Calibration. DICTA Doreen Altinay, Andrew P. Bradley, Andrew Mehnert
2010	J	`jnl`	Rule extraction from support vector machines: A review. Neurocomputing Nahla H. Barakat, Andrew P. Bradley
2009	Misc	`conf`	Feature and Classifier Selection for Automatic Classification of Lesions in Dynamic Contrast-Enhanced MRI of the Breast. DICTA Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Dominic Kennedy, Stuart Crozier
2009	—	`conf`	The Effect of Domain Knowledge on Rule Extraction from Support Vector Machines. MLDM Nahla H. Barakat, Andrew P. Bradley
2008	B	`conf`	Group-based meta-classification. ICPR Noor Azah Samsudin, Andrew P. Bradley
2008	B	`conf`	Mixed content image compression by gradient field integration. ICIP Peter W. M. Ilbery, David Taubman, Andrew P. Bradley
2007	C	`conf`	A Comparison of DCT and DWT Block Based Watermarking on Medical Image Quality. IWDW Jason Dowling, Birgit M. Planitz, Anthony J. Maeder, Jiang Du, Binh Pham, Colin Boyd, Shaokang Chen, Andrew P. Bradley, Stuart Crozier
2007	Misc	`conf`	Automatic Segmentation of Enhancing Breast Tissue in Dynamic Contrast-Enhanced MR Images. DICTA Yaniv Gal, Andrew Mehnert, Andrew P. Bradley, Kerry McMahon, Stuart Crozier
2007	J	`jnl`	Correspondence-Free Determination of the Affine Fundamental Matrix. IEEE Trans. Pattern Anal. Mach. Intell. Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson, John Williams, Peter J. Kootsookos
2007	J	`jnl`	Rule Extraction from Support Vector Machines: A Sequential Covering Approach. IEEE Trans. Knowl. Data Eng. Nahla H. Barakat, Andrew P. Bradley
2006	—	`conf`	Estimation Of Epipolar Geometry Via The Radon Transform. ICASSP (2) Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson
2006	—	`conf`	Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve. ICPR (2) Nahla H. Barakat, Andrew P. Bradley
2005	Misc	`conf`	Towards Optimal Image Stitching for Virtual Microscopy. DICTA Ben Appleton, Andrew P. Bradley, Michael Wildermoth
2005	Misc	`conf`	Virtual Microscopy with Extended Depth of Field. DICTA Andrew P. Bradley, Michael Wildermoth, Paul Mills
2004	—	`conf`	Sample Size Estimation using the Receiver Operating Characteristic Curve. ICPR (4) Andrew P. Bradley, I. Dennis Longstaff
2003	Misc	`conf`	Shift-invariance in the Discrete Wavelet Transform. DICTA Andrew P. Bradley
2003	J	`jnl`	Visual attention for region of interest coding in JPEG 2000. J. Vis. Commun. Image Represent. Andrew P. Bradley, Fred Stentiford
1999	J	`jnl`	A wavelet visible difference predictor. IEEE Trans. Image Process. Andrew P. Bradley
1998	J	`jnl`	Perceptual quality metrics applied to still image compression. Signal Process. Michael P. Eckert, Andrew P. Bradley
1997	J	`jnl`	The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit. Andrew P. Bradley
1996	—	`—`	Machine learning for medical diagnostics: techniques for feature extraction, classification, and evaluation Andrew P. Bradley
1996	J	`jnl`	ROC curves and the X Pattern Recognit. Lett. Andrew P. Bradley
1996	J	`jnl`	The Multiscale Classifier. IEEE Trans. Pattern Anal. Mach. Intell. Brian C. Lovell, Andrew P. Bradley