| Histopathological image analysis: A review MN Gurcan, LE Boucheron, A Can, A Madabhushi, NM Rajpoot, B Yener IEEE reviews in biomedical engineering 2, 147-171, 2009 | 1374 | 2009 |
| Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases A Janowczyk, A Madabhushi Journal of pathology informatics 7, 2016 | 584 | 2016 |
| Stacked sparse autoencoder (SSAE) for nuclei detection on breast cancer histopathology images J Xu, L Xiang, Q Liu, H Gilmore, J Wu, J Tang, A Madabhushi IEEE transactions on medical imaging 35 (1), 119-130, 2015 | 511 | 2015 |
| Image analysis and machine learning in digital pathology: Challenges and opportunities A Madabhushi, G Lee Medical image analysis 33, 170-175, 2016 | 364 | 2016 |
| Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions A Madabhushi, DN Metaxas IEEE transactions on medical imaging 22 (2), 155-169, 2003 | 352 | 2003 |
| Digital imaging in pathology: whole-slide imaging and beyond F Ghaznavi, A Evans, A Madabhushi, M Feldman Annual Review of Pathology: Mechanisms of Disease 8, 331-359, 2013 | 328 | 2013 |
| 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 | 323 | 2008 |
| Assessment of algorithms for mitosis detection in breast cancer histopathology images M Veta, PJ Van Diest, SM Willems, H Wang, A Madabhushi, A Cruz-Roa, ... Medical image analysis 20 (1), 237-248, 2015 | 320 | 2015 |
| Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge G Litjens, R Toth, W van de Ven, C Hoeks, S Kerkstra, B van Ginneken, ... Medical image analysis 18 (2), 359-373, 2014 | 318 | 2014 |
| A deep convolutional neural network for segmenting and classifying epithelial and stromal regions in histopathological images J Xu, X Luo, G Wang, H Gilmore, A Madabhushi Neurocomputing 191, 214-223, 2016 | 309 | 2016 |
| Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks A Cruz-Roa, A Basavanhally, F González, H Gilmore, M Feldman, ... Medical Imaging 2014: Digital Pathology 9041, 904103, 2014 | 308 | 2014 |
| A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection AA Cruz-Roa, JEA Ovalle, A Madabhushi, FAG Osorio International Conference on Medical Image Computing and Computer-Assisted …, 2013 | 291 | 2013 |
| 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 | 284 | 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 | 278 | 2007 |
| Applications of machine learning in drug discovery and development J Vamathevan, D Clark, P Czodrowski, I Dunham, E Ferran, G Lee, B Li, ... Nature Reviews Drug Discovery 18 (6), 463-477, 2019 | 267 | 2019 |
| Computerized image-based detection and grading of lymphocytic infiltration in HER2+ breast cancer histopathology AN Basavanhally, S Ganesan, S Agner, JP Monaco, MD Feldman, ... IEEE Transactions on biomedical engineering 57 (3), 642-653, 2009 | 258 | 2009 |
| 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 | 246 | 2010 |
| Identification of a microRNA panel for clear-cell kidney cancer D Juan, G Alexe, T Antes, H Liu, A Madabhushi, C Delisi, S Ganesan, ... Urology 75 (4), 835-841, 2010 | 243 | 2010 |
| Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features H Wang, AC Roa, AN Basavanhally, HL Gilmore, N Shih, M Feldman, ... Journal of Medical Imaging 1 (3), 034003, 2014 | 227 | 2014 |
| Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent A Cruz-Roa, H Gilmore, A Basavanhally, M Feldman, S Ganesan, ... Scientific reports 7, 46450, 2017 | 226 | 2017 |
Michael D FeldmanUniversity of PennsylavniaVerified email at mail.med.upenn.edu
