A. Bradley

I. Vaughan L. Clarkson, Andrew P. Bradley, Stefan Lehmann, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Enhancing the classification accuracy of Steady-State Visual Evoked Potential-based Brain-Computer Interface using Component Synchrony Measure

Andrew P. Bradley, Ross Cunnington, Kian B. Ng, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Stimulus specificity of a steady-state visual-evoked potential-based brain–computer interface

Ross Cunnington, Andrew P Bradley, Kian B. Ng, 2012, Journal of neural engineering.

On the benefits of using chained stimuli for frequency-specific ABR acquisition

Matthew A. Petoe, Andrew P. Bradley, Wayne J. Wilson, 2009 .

Multisite accelerometry for sleep and wake classification in children

Marnie L. Lamprecht, Andrew P Bradley, A. Bradley, 2015, Physiological measurement.

Rule extraction from support vector machines: A review

Andrew P. Bradley, Nahla H. Barakat, A. Bradley, 2010, Neurocomputing.

The performance of a variable-flow indirect calorimeter.

A. Bradley, P. Beatty, I. Campbell, 1996, Physiological measurement.

Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework

G. Carneiro, L. Palmer, A. Bradley, 2017, Scientific Reports.

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning

Andrew P. Bradley, Gustavo Carneiro, Jacinto Nascimento, 2017, IEEE Transactions on Medical Imaging.

Performance Analysis of Three Microscope Slide Scanning Techniques

Yaniv Gal, Andrew P. Bradley, Yilun Fan, 2013, 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Three-Point Search Algorithm for Video Compression

Z. Q. Cai, V. N. Tran, A. Bradley, 1996, Fourth International Symposium on Signal Processing and Its Applications.

A wavelet visible difference predictor

Andrew P. Bradley, A. Bradley, 1999, IEEE Trans. Image Process..

Modeling of a rotary blood pump.

Andrew P Bradley, Daniel L Timms, Frank Nestler, 2014, Artificial organs.

The Multiscale Classifier

Brian C. Lovell, Andrew P. Bradley, B. Lovell, 1996, IEEE Trans. Pattern Anal. Mach. Intell..

Deep Learning and Data Labeling for Medical Applications

Jaime S. Cardoso, João Paulo Papa, Julien Cornebise, 2016, Lecture Notes in Computer Science.

A deep learning approach for the analysis of masses in mammograms with minimal user intervention

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2017, Medical Image Anal..

Temporal associations between arousal and body/limb movement in children with suspected obstructed sleep apnoea

Marnie L. Lamprecht, A. Bradley, P. Terrill, 2016, Physiological measurement.

Training Medical Image Analysis Systems like Radiologists pdf

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2018, MICCAI.

Fully automated classification of mammograms using deep residual neural networks

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Fully Automatic Computer-aided Mass Detection and Segmentation via Pseudo-color Mammograms and Mask R-CNN

Stuart Crozier, Samuel Kelly, Andrew P Bradley, 2019, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2017, MICCAI.

The Automated Learning of Deep Features for Breast Mass Classification from Mammograms

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2016, MICCAI.

How to Exploit Weaknesses in Biomedical Challenge Design and Organization

Lena Maier-Hein, Annika Reinke, Patrick Scholz, 2018, MICCAI.

Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1

Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, 2017, Deep Learning for Medical Image Analysis.

Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2015, 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2015, MICCAI.

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions pdf

Alejandro F. Frangi, Peter F. Neher, Klaus H. Maier-Hein, 2018, ArXiv.

Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means

Stuart Crozier, Andrew Mehnert, Dominic Kennedy, 2010, IEEE Transactions on Medical Imaging.

A Comparison of DCT and DWT Block Based Watermarking on Medical Image Quality

Stuart Crozier, Colin Boyd, Jason Dowling, 2008, IWDW.

A Parametric Simulation of Neuronal Noise From Microelectrode Recordings

Andrew P. Bradley, John J. Varghese, Peter A. Silburn, 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Efficient micro-electrode recording modeling using a filtered point process

J. J. Varghese, P. Meehan, P. Silburn, 2013, 1307.5250.

Editorial

Gustavo Carneiro, Jaime S. Cardoso, Zhi Lu, 1875, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2018, Medical Image Anal..

Spikes from compound action potentials in simulated microelectrode recordings

Andrew P. Bradley, Kristian J. Weegink, John J. Varghese, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Intelligible Support Vector Machines for Diagnosis of Diabetes Mellitus

Andrew P. Bradley, Nahla H. Barakat, Mohamed Nabil H. Barakat, 2010, IEEE Transactions on Information Technology in Biomedicine.

An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells

Gustavo Carneiro, Zhi Lu, Andrew P. Bradley, 2015, IEEE Transactions on Image Processing.

Visual attention for region of interest coding in JPEG 2000

Fred Stentiford, Andrew P. Bradley, A. Bradley, 2003, J. Vis. Commun. Image Represent..

Spectral and synchrony differences in auditory brainstem responses evoked by chirps of varying durations.

W. Wilson, A. Bradley, M. Petoe, 2010, The Journal of the Acoustical Society of America.

Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior

Gustavo Carneiro, Andrew P. Bradley, Gabriel Maicas, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps

Olivier Salvado, Clinton Fookes, Pierrick Bourgeat, 2020, SASHIMI@MICCAI.

Multi-scale sifting for mammographic mass detection and segmentation

Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra, 2019, Biomedical Physics & Engineering Express.

Rule Extraction from Support Vector Machines: A Sequential Covering Approach

Andrew P. Bradley, Nahla H. Barakat, A. Bradley, 2007, IEEE Transactions on Knowledge and Data Engineering.

Physiological control of dual rotary pumps as a biventricular assist device using a master/slave approach.

Stephen Wilson, John Fraser, Andrew Bradley, 2014, Artificial organs.

Conducting shorter VEP tests to estimate visual acuity via assessment of SNR

Andrew P. Bradley, Kartik K. Iyer, Stephen J. Wilson, 2013, Documenta Ophthalmologica.

Automated Segmentation of Skin Strata in Reflectance Confocal Microscopy Depth Stacks

Andrew P. Bradley, Tarl W. Prow, H. Peter Soyer, 2015, bioRxiv.

Use of pulse transit time to distinguish respiratory events from tidal breathing in sleeping children.

Andrew P Bradley, Stephen J Wilson, A. Bradley, 2005, Chest.

Progress towards Universal Neonatal Hearing Screening: A World Review

W. Wilson, A. Bradley, Julie Tann, 2009 .

Anne L. Martel, Marc Combalia, Veronica Vilaplana, 2018, DLMIA/ML-CDS@MICCAI.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support pdf

Jaime S. Cardoso, Mitko Veta, Josien P. W. Pluim, 2017, Lecture Notes in Computer Science.

Multi-scale mass segmentation for mammograms via cascaded random forests

Stuart Crozier, Andrew P. Bradley, Neeraj Dhungel, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells

Gustavo Carneiro, Zhi Lu, Andrew P. Bradley, 2013, MICCAI.

Machine learning for medical diagnostics: Techniques for feature extraction, classification, and evaluation

Andrew P. Bradley, A. Bradley, 1996 .

Classification in scale-space: Applications to texture analysis

Brian C. Lovell, Andrew P. Bradley, Paul Jackway, 1995 .

Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework

Lyle J. Palmer, Andrew P. Bradley, Jacinto C. Nascimento, 2017, Scientific Reports.

Feature and Classifier Selection for Automatic Classification of Lesions in Dynamic Contrast-Enhanced MRI of the Breast

Stuart Crozier, Andrew Mehnert, Dominic Kennedy, 2009, 2009 Digital Image Computing: Techniques and Applications.

Teaching histology to first-year veterinary science students using virtual microscopy and traditional microscopy: a comparison of student responses.

Paul C Mills, Michael Wildermoth, Andrew P Bradley, 2007, Journal of veterinary medical education.

Sample size estimation using the receiver operating characteristic curve

Andrew P. Bradley, Ian Dennis Longstaff, I. Longstaff, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

The Effects of Electrode Montage on the Amplitude of Wave V in the Auditory Brainstem Response to Maximum Length Sequence Stimuli

W. Wilson, A. Bradley, M. Petoe, 2007, Audiology and Neurotology.

Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology

Stephen E. Rose, Andrew P. Bradley, Alex M. Pagnozzi, 2015, 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Estimation of neuronal firing rates with the three-state biological point process model

Andrew P. Bradley, Helen J. Chenery, Peter A. Silburn, 2008, Journal of Neuroscience Methods.

Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care

Aaron Carass, Keno März, Lena Maier-Hein, 2019, Nature Communications.

Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography

Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley, 2016, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Over-Complete Discrete Wavelet Transformation of the Normal Auditory Brainstem Response Improves Prediction of Outcome following Severe Acute Closed Head Injury

W. Wilson, A. Bradley, R. Darnell, 2006, Audiology and Neurotology.

Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

I. Reid, G. Carneiro, A. Bradley, 2018, Medical Image Anal..

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI pdf

Stuart Crozier, Andrew P. Bradley, Darryl McClymont, 2020, Biomedical physics & engineering express.

Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI

Ian D. Reid, Gabriel Maicas, Gustavo Carneiro, 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.

Model Agnostic Saliency For Weakly Supervised Lesion Detection From Breast DCE-MRI

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2018, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Lesion Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI

Gustavo Carneiro, Ian Reid, Andrew P. Bradley, 2018 .

Rule extraction from support vector machines: A review

Nahla H. Barakat, A. Bradley, 2010, Neurocomputing.

Editorial

Jaime S. Cardoso, J. Tavares, G. Carneiro, 2023 .

A hybrid mock circulation loop for a total artificial heart.

Andrew P Bradley, Daniel L Timms, Frank Nestler, 2014, Artificial organs.

Physiologic parameters that affect pulse transit time difference between the upper and lower limbs in children

A. Bradley, J. Foo, S. J. Wilson, 2006, Journal of Human Hypertension.

ROC curves and the X2 test

A. Bradley, 1996, Pattern Recognit. Lett..

Nearest neighbour group-based classification

Andrew P. Bradley, Noor Azah Samsudin, A. Bradley, 2010, Pattern Recognit..

The filtered words test and the influence of lexicality.

Andrew E. Smith, W. Wilson, A. Bradley, 2014, Journal of speech, language, and hearing research : JSLHR.