Andrew P. Bradley

发表

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

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

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..

Ethics and data mining in biomedical engineering

Andrew P. Bradley, 2013 .

Deep structured learning for mass segmentation from mammograms

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2014, 2015 IEEE International Conference on Image Processing (ICIP).

Training Medical Image Analysis Systems like Radiologists pdf

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

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

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

2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Noosa, QLD, Australia, December 6-8, 2011

Yaniv Gal, Andrew P. Bradley, Paul Jackway, 2011, DICTA.

Extended Naïve Bayes for Group Based Classification

Andrew P. Bradley, Noor Azah Samsudin, 2014, SCDM.

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.

Characterization of movements during restless sleep in children: A pilot study

Andrew P. Bradley, Philip I. Terrill, Marnie L. Lamprecht, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

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).

Illumination Effects in Quantitative Virtual Microscopy

Andrew P. Bradley, Doreen Altinay, 2013, CAIP.

JPEG 2000 and Region of Interest Coding

Fred Stentiford, Andrew P. Bradley, 2002 .

Towards Optimal Image Stitching for Virtual Microscopy

Andrew P. Bradley, Ben Appleton, Michael Wildermoth, 2005, Digital Image Computing: Techniques and Applications (DICTA'05).

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

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

A wavelet visible difference predictor

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

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

Alejandro F. Frangi, Peter F. Neher, Aaron Carass, 2018, Nature Communications.

Investigation of the non-Markovity Spectrum as a Cognitive Processing Measure of Deep Brain Microelectrode Recordings

Andrew P. Bradley, P. A. Bellette, John J. Varghese, 2011, BIOSIGNALS.

On the methodology for comparing learning algorithms: a case

Brian C. Lovell, Andrew P. Bradley, M. Ray, 1994, Proceedings of ANZIIS '94 - Australian New Zealnd Intelligent Information Systems Conference.

Evaluation of a morphological filter in mean cardiac output determination: application to left ventricular assist devices

Andrew P. Bradley, Stephen J. Wilson, David G. Mason, 2013, Medical & Biological Engineering & Computing.

Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells

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

Producing Radiologist-Quality Reports for Interpretable Deep Learning.

Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Inductive Learning using Multiscale Classification

Brian C. Lovell, Andrew P. Bradley, 1994 .

Perceptual quality metrics applied to still image compression

Andrew P. Bradley, Michael P. Eckert, A. Bradley, 1998, Signal Process..

Ethics for Biomedical Engineers

Andrew P. Bradley, Stephen J. Wilson, Jong Yong Abdiel Foo, 2013, Springer New York.

Effect of posterized naturalistic stimuli on SSVEP-based BCI

Andrew P. Bradley, Ross Cunnington, Kian B. Ng, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Registration evaluation of dynamic breast MR images

Stuart Crozier, Andrew Mehnert, Dominic Kennedy, 2005 .

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..

Group-based meta-classification

Andrew P. Bradley, Noor Azah Samsudin, 2008, 2008 19th International Conference on Pattern Recognition.

Producing radiologist-quality reports for interpretable artificial intelligence pdf

Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley, 2018, ArXiv.

Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models

Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, 2015, MICCAI.

Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells

Ghassan Hamarneh, Andrew P. Bradley, Gustavo Carneiro, 2017, IEEE Journal of Biomedical and Health Informatics.

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).

Estimation Of Epipolar Geometry Via The Radon Transform

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

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).

The Multiscale Classifier

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

ROC curves and the X2 test

Andrew P. Bradley, 1996, Pattern Recognit. Lett..

Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach pdf

Gustavo Carneiro, Zhi Lu, Andrew P. Bradley, 2016, ArXiv.

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).

An Evaluation of Multi-resolution Microscope Slide Scanning Algorithms

Andrew P. Bradley, Doreen Altinay, 2011, 2011 International Conference on Digital Image Computing: Techniques and Applications.

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

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

Nearest neighbour group-based classification

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

Vefahren for data compression

Andrew P. Bradley, James Philip Andrew, J. Andrew, 1998 .

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.

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

Gustavo Carneiro, Jaime S. Cardoso, M. Jorge Cardoso, 2017, Lecture Notes in Computer Science.

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

Andrew P. Bradley, A. Bradley, 1996 .

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).

Microscopic specimen delineation using auto-phase correlation index

Yaniv Gal, Andrew P. Bradley, Yilun Fan, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Multiple instance learning for breast MRI based on generic spatio-temporal features

Andrew P. Bradley, Fahira A. Maken, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Comparison of Multiple Instance and Group Based Learning

Andrew P. Bradley, Steven D. Brossi, 2012, 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA).

1st MICCAI workshop on deep learning in medical image analysis

Gustavo Carneiro, Jaime S. Cardoso, Zhi Lu, 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

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).

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.

Visual attention for region of interest coding in JPEG 2000

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

Classification in scale-space: Applications to texture analysis

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

The Effect of Domain Knowledge on Rule Extraction from Support Vector Machines

Andrew P. Bradley, Nahla H. Barakat, 2009, MLDM.

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).

Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

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).

A preliminary investigation of the effects of different type of training in Auditory Brainstem Response (ABR) waveform analysis among audiology students

Andrew P. Bradley, Wayne J. Wilson, Ahmad Aidil Arafat Dzulkarnain, 2014 .

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

Gustavo Carneiro, João Paulo Papa, Lena Maier-Hein, 2018, DLMIA/ML-CDS@MICCAI.

The use of the area under the ROC curve in the evaluation of machine learning algorithms

Andrew P. Bradley, A. Bradley, 1997, Pattern Recognit..

Spectral properties of neuronal pulse interval modulation

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

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.

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).

On the Estimation of Extrinsic and Intrinsic Parameters of Optical Microscope Calibration

Andrew Mehnert, Andrew P. Bradley, Doreen Altinay, 2010, 2010 International Conference on Digital Image Computing: Techniques and Applications.

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning

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

Rapid universal neonatal hearing screening using a fast automatic auditory brainstem response device

Andrew P. Bradley, Matthew A. Petoe, Wayne J. Wilson, 2008 .

How to Exploit Weaknesses in Biomedical Challenge Design and Organization

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

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.

Visual quality assessment of watermarked medical images

Stuart Crozier, Colin Boyd, Andrew P. Bradley, 2007, SPIE Medical Imaging.

Rule extraction from support vector machines: A review

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

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

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

Classification In Scale-Space: Applications To Texture

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

Automatic Segmentation of Enhancing Breast Tissue in Dynamic Contrast-Enhanced MR Images

Stuart Crozier, Andrew Mehnert, Yaniv Gal, 2007, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007).

Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms

Gustavo Carneiro, Andrew P. Bradley, Neeraj Dhungel, 2017, Deep Learning and Convolutional Neural Networks for Medical Image Computing.

Half-AUC for the evaluation of sensitive or specific classifiers

Andrew P. Bradley, A. Bradley, 2014, Pattern Recognit. Lett..

Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features

Gustavo Carneiro, Jaime S. Cardoso, Andrew P. Bradley, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Automated Segmentation of Skin Strata in Reflectance Confocal Microscopy Depth Stacks

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

Effect of competing stimuli on SSVEP-based BCI

Andrew P. Bradley, Ross Cunnington, Kian B. Ng, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Player Tracking and Stroke Recognition in Tennis Video

Andrew P. Bradley, T. Bloom, 2003 .

Multi-scale sifting for mammographic mass detection and segmentation

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

Fast Automated Auditory Brainstem Response (AABR) using new non linear Maximum Length Sequence (MLS) reconstruction and automated signal detection (Ujian respon auditori batang otak automatik yang cepat menggunakan Non Linear Maximum Length Sequence (MLS) Reconstruction dan Automated Signal Detectio

Andrew P. Bradley, Matthew A. Petoe, Sarah Rahmat, 2010 .

Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve

Andrew P. Bradley, Nahla H. Barakat, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Editorial

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

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

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

Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels

Andrew P. Bradley, Tarl W. Prow, H. Peter Soyer, 2015, 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Special issue: 4th MICCAI workshop on deep learning in medical image analysis

Gustavo Carneiro, Zhi Lu, João Paulo Papa, 2020, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Scale-Space Texture Analysis

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

Detecting hip fractures with radiologist-level performance using deep neural networks pdf

Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley, 2017, ArXiv.

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.

Virtual Microscopy with Extended Depth of Field

Paul Mills, Andrew P. Bradley, Michael Wildermoth, 2005, Digital Image Computing: Techniques and Applications (DICTA'05).

Access the IEEE Computer Society Digital Library [advertisement]

Andrew P. Bradley, Nahla Barakat, 2007 .

Deep Learning and Data Labeling for Medical Applications

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

ROC curve equivalence using the Kolmogorov-Smirnov test

Andrew P. Bradley, A. Bradley, 2013, Pattern Recognit. Lett..

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.

Shift-invariance in the Discrete Wavelet Transform

Andrew P. Bradley, 2003, DICTA.

Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging

Yaniv Gal, Andrew P. Bradley, Darryl McClymont, 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

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.

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..

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).

Automated segmentation of skin strata in reflectance confocal microscopy depth stacks

Andrew P. Bradley, Tarl W. Prow, Samuel C. Hames, 2015, bioRxiv.

Correspondence-Free Determination of the Affine Fundamental Matrix

I. Vaughan L. Clarkson, Andrew P. Bradley, Peter J. Kootsookos, 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Cost-Sensitive Decision Tree Pruning: Use of the ROC Curve

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

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.

Can Region of Interest Coding Improve Overall Perceived Image Quality

Andrew P. Bradley, A. Bradley, 2003 .

Active Contour Model Based Segmentation of Colposcopy Images of Cervix Uteri Using Gaussian Pyramids

Andrew P. Bradley, Viara Van Raad, 2002 .