Andrew P. Bradley

Publication Activity (10 Years)

Years Active: 1996-2023
Publications (10 Years): 41

Top Topics

Confusion Matrix

Medical Image Analysis

Top Venues

Publications

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)
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)
Salamata Konate, Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Andrew P. Bradley, Olivier Salvado
Bias Identification with RankPix Saliency. ICASSP (2023)
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)
David R. Lovell, Dimity Miller, Jaiden Capra, Andrew P. Bradley
Never mind the metrics - what about the uncertainty? Visualising confusion matrix metric distributions. CoRR (2022)
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)
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 (2022)
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)
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)
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)
David Lovell, Bridget McCarron, Brendan Langfield, Khoa Tran, Andrew P. Bradley
Taking the Confusion Out of Multinomial Confusion Matrices and Imbalanced Classes. AusDM (2021)
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) (2020)
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)
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 (2020)
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)
William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley
Producing Radiologist-Quality Reports for Interpretable Deep Learning. ISBI (2019)
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 (2019)
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) (2019)
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)
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)
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 (2018)
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro
Training Medical Image Analysis Systems like Radiologists. MICCAI (1) (2018)
William Gale, Luke Oakden-Rayner, Gustavo Carneiro, Andrew P. Bradley, Lyle J. Palmer
Producing radiologist-quality reports for interpretable artificial intelligence. CoRR (2018)
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)
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) (2018)
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 (2018)
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro
Training Medical Image Analysis Systems like Radiologists. CoRR (2018)
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 (2018)
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)
Hang Min, Shekhar S. Chandra, Neeraj Dhungel, Stuart Crozier, Andrew P. Bradley
Multi-scale mass segmentation for mammograms via cascaded random forests. ISBI (2017)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Fully automated classification of mammograms using deep residual neural networks. ISBI (2017)
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 (2017)
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 (2017)
Gabriel Maicas, Gustavo Carneiro, Andrew P. Bradley
Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior. ISBI (2017)
Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley
Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning. IEEE Trans. Medical Imaging 36 (11) (2017)
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)
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)
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) (2017)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. MICCAI (2) (2016)
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 (2016)
Zhi Lu, Gustavo Carneiro, Neeraj Dhungel, Andrew P. Bradley
Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach. CoRR (2016)
Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley
Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models. MICCAI (3) (2015)
Fahira Afzal Maken, Andrew P. Bradley
Multiple instance learning for breast MRI based on generic spatio-temporal features. ICASSP (2015)
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)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms. ISBI (2015)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms. MICCAI (1) (2015)
Samuel C. Hames, Marco Ardigò, H. Peter Soyer, Andrew P. Bradley, Tarl W. Prow
Segmentation of skin strata in reflectance confocal microscopy depth stacks. Medical Imaging: Image Processing (2015)
John J. Varghese, Kristian J. Weegink, P. A. Bellette, Andrew P. Bradley
Spectral properties of neuronal pulse interval modulation. ICASSP (2015)
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) (2015)
Kristian J. Weegink, John J. Varghese, Andrew P. Bradley
Spikes from compound action potentials in simulated microelectrode recordings. ICASSP (2015)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Deep structured learning for mass segmentation from mammograms. ICIP (2015)
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)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests. DICTA (2015)
Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley
Deep Structured learning for mass segmentation from Mammograms. CoRR (2014)
Yilun Fan, Yaniv Gal, Andrew P. Bradley
Microscopic specimen delineation using auto-phase correlation index. ISBI (2014)
Andrew P. Bradley
Half-AUC for the evaluation of sensitive or specific classifiers. Pattern Recognit. Lett. 38 (2014)
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)
Noor Azah Samsudin, Andrew P. Bradley
Extended Naïve Bayes for Group Based Classification. SCDM (2014)
Fahira A. Maken, Yaniv Gal, Darryl McClymont, Andrew P. Bradley
Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging. DICTA (2014)
Yilun Fan, Yaniv Gal, Andrew P. Bradley
Performance Analysis of Three Microscope Slide Scanning Techniques. DICTA (2013)
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) (2013)
Andrew P. Bradley
ROC curve equivalence using the Kolmogorov-Smirnov test. Pattern Recognit. Lett. 34 (5) (2013)
Doreen Altinay, Andrew P. Bradley
Illumination Effects in Quantitative Virtual Microscopy. CAIP (2) (2013)
Kian B. Ng, Andrew P. Bradley, Ross Cunnington
Effect of posterized naturalistic stimuli on SSVEP-based BCI. EMBC (2013)
Zhi Lu, Gustavo Carneiro, Andrew P. Bradley
Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells. MICCAI (1) (2013)
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)
Steven D. Brossi, Andrew P. Bradley
A Comparison of Multiple Instance and Group Based Learning. DICTA (2012)
Kian B. Ng, Andrew P. Bradley, Ross Cunnington
Effect of competing stimuli on SSVEP-based BCI. EMBC (2011)
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)
Doreen Altinay, Andrew P. Bradley
An Evaluation of Multi-resolution Microscope Slide Scanning Algorithms. DICTA (2011)
Nahla H. Barakat, Andrew P. Bradley
Rule extraction from support vector machines: A review. Neurocomputing 74 (1-3) (2010)
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) (2010)
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) (2010)
Noor Azah Samsudin, Andrew P. Bradley
Nearest neighbour group-based classification. Pattern Recognit. 43 (10) (2010)
Doreen Altinay, Andrew P. Bradley, Andrew Mehnert
On the Estimation of Extrinsic and Intrinsic Parameters of Optical Microscope Calibration. DICTA (2010)
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)
Nahla H. Barakat, Andrew P. Bradley
The Effect of Domain Knowledge on Rule Extraction from Support Vector Machines. MLDM (2009)
Noor Azah Samsudin, Andrew P. Bradley
Group-based meta-classification. ICPR (2008)
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)
Nahla H. Barakat, Andrew P. Bradley
Rule Extraction from Support Vector Machines: A Sequential Covering Approach. IEEE Trans. Knowl. Data Eng. 19 (6) (2007)
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)
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) (2007)
Stefan Lehmann, Andrew P. Bradley, I. Vaughan L. Clarkson
Estimation Of Epipolar Geometry Via The Radon Transform. ICASSP (2) (2006)
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)
Andrew P. Bradley, Michael Wildermoth, Paul Mills
Virtual Microscopy with Extended Depth of Field. DICTA (2005)
Ben Appleton, Andrew P. Bradley, Michael Wildermoth
Towards Optimal Image Stitching for Virtual Microscopy. DICTA (2005)
Andrew P. Bradley, I. Dennis Longstaff
Sample Size Estimation using the Receiver Operating Characteristic Curve. ICPR (4) (2004)
Andrew P. Bradley, Fred Stentiford
Visual attention for region of interest coding in JPEG 2000. J. Vis. Commun. Image Represent. 14 (3) (2003)
Andrew P. Bradley
Shift-invariance in the Discrete Wavelet Transform. DICTA (2003)
Andrew P. Bradley
A wavelet visible difference predictor. IEEE Trans. Image Process. 8 (5) (1999)
Michael P. Eckert, Andrew P. Bradley
Perceptual quality metrics applied to still image compression. Signal Process. 70 (3) (1998)
Andrew P. Bradley
The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit. 30 (7) (1997)
Brian C. Lovell, Andrew P. Bradley
The Multiscale Classifier. IEEE Trans. Pattern Anal. Mach. Intell. 18 (2) (1996)
Andrew P. Bradley
test. Pattern Recognit. Lett. 17 (3) (1996)