| Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology S Naik, S Doyle, S Agner, A Madabhushi, M Feldman, J Tomaszewski 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to …, 2008 | 454 | 2008 |
| Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features S Doyle, S Agner, A Madabhushi, M Feldman, J Tomaszewski 2008 5th IEEE international symposium on biomedical imaging: from nano to …, 2008 | 388 | 2008 |
| Automated grading of prostate cancer using architectural and textural image features S Doyle, M Hwang, K Shah, A Madabhushi, M Feldman, J Tomaszeweski 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to …, 2007 | 337 | 2007 |
| A boosted Bayesian multiresolution classifier for prostate cancer detection from digitized needle biopsies S Doyle, M Feldman, J Tomaszewski, A Madabhushi IEEE transactions on biomedical engineering 59 (5), 1205-1218, 2010 | 314 | 2010 |
| A boosting cascade for automated detection of prostate cancer from digitized histology S Doyle, A Madabhushi, M Feldman, J Tomaszeweski Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006: 9th …, 2006 | 167 | 2006 |
| Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data A Madabhushi, S Agner, A Basavanhally, S Doyle, G Lee Computerized medical imaging and graphics 35 (7-8), 506-514, 2011 | 164 | 2011 |
| Gland segmentation and computerized gleason grading of prostate histology by integrating low-, high-level and domain specific information S Naik, S Doyle, M Feldman, J Tomaszewski, A Madabhushi MIAAB workshop, 1-8, 2007 | 157 | 2007 |
| Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer S Doyle, MD Feldman, N Shih, J Tomaszewski, A Madabhushi BMC bioinformatics 13, 1-15, 2012 | 133 | 2012 |
| Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer J Whitney, G Corredor, A Janowczyk, S Ganesan, S Doyle, ... BMC cancer 18, 1-15, 2018 | 100 | 2018 |
| Active deep learning: Improved training efficiency of convolutional neural networks for tissue classification in oral cavity cancer J Folmsbee, X Liu, M Brandwein-Weber, S Doyle 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018 | 92 | 2018 |
| An active learning based classification strategy for the minority class problem: application to histopathology annotation S Doyle, J Monaco, M Feldman, J Tomaszewski, A Madabhushi BMC bioinformatics 12, 1-14, 2011 | 89 | 2011 |
| A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images A Janowczyk, S Doyle, H Gilmore, A Madabhushi Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018 | 74 | 2018 |
| Malignancy diagnosis using content-based image retreival of tissue histopathology A Madabhushi, S Doyle, MD Feldman, JE Tomaszewski US Patent 8,280,132, 2012 | 62 | 2012 |
| Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach S Doyle, C Rodriguez, A Madabhushi, J Tomaszeweski, M Feldman 2006 International Conference of the IEEE Engineering in Medicine and …, 2006 | 58 | 2006 |
| Role of training data variability on classifier performance and generalizability R Therrien, S Doyle Medical Imaging 2018: Digital Pathology 10581, 58-70, 2018 | 53 | 2018 |
| Towards improved cancer diagnosis and prognosis using analysis of gene expression data and computer aided imaging G Alexe, J Monaco, S Doyle, A Basavanhally, A Reddy, M Seiler, ... Experimental Biology and Medicine 234 (8), 860-879, 2009 | 52 | 2009 |
| Integrated diagnostics: a conceptual framework with examples A Madabhushi, S Doyle, G Lee, A Basavanhally, J Monaco, S Masters, ... Clinical chemistry and laboratory medicine 48 (7), 989-998, 2010 | 50 | 2010 |
| Biomedical imaging ontologies: A survey and proposal for future work B Smith, S Arabandi, M Brochhausen, M Calhoun, P Ciccarese, S Doyle, ... Journal of pathology informatics 6 (1), 37, 2015 | 45 | 2015 |
| Gland segmentation and gleason grading of prostate histology by integrating low-, high-level and domain specific information S Naik, S Doyle, A Madabhushi, J Tomaszewski, M Feldman Workshop on Microscopic Image Analysis with Applications in Biology 180, 2007 | 44 | 2007 |
| A knowledge representation framework for integration, classification of multi-scale imaging and non-imaging data: Preliminary results in predicting prostate cancer recurrence … G Lee, S Doyle, J Monaco, A Madabhushi, MD Feldman, SR Master, ... 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2009 | 43 | 2009 |
