Anant Madabhushi

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Michael D FeldmanIndiana UniversityAdresse e-mail validée de iu.edu
Kaustav BeraDepartment of Radiology, University Hospitals Cleveland, Case Western Reserve UniversityAdresse e-mail validée de case.edu
Pallavi TiwariAssociate Professor, Department of Radiology & Biomedical Engineering, UW-MadisonAdresse e-mail validée de wisc.edu
Andrew JanowczykEmory UniversityAdresse e-mail validée de emory.edu
Prateek PrasannaAssistant Professor, Stony Brook UniversityAdresse e-mail validée de stonybrook.edu
Vamsidhar Velcheti MD FACP FCCPYale UniversityAdresse e-mail validée de yale.edu
Satish E. ViswanathCase Western Reserve University, Department of Biomedical EngineeringAdresse e-mail validée de case.edu
Pingfu FuCase Western Reserve UniversityAdresse e-mail validée de case.edu
Ajay BasavanhallyCase Western Reserve UniversityAdresse e-mail validée de case.edu
George LeeBristol-Myers SquibbAdresse e-mail validée de bms.com
Shridar GanesanProfessor of Medicine, Rutgers Cancer Institute of New JerseyAdresse e-mail validée de cinj.rutgers.edu
Nathaniel BramanPicture HealthAdresse e-mail validée de case.edu
Niha Beig, PhDCase Western Reserve UniversityAdresse e-mail validée de case.edu
Scott DoyleThe University at BuffaloAdresse e-mail validée de buffalo.edu
B. Nicolas BlochProfessor of Radiology & Urology UMass Memorial Medical Center & UMass Medical School • Professor ofAdresse e-mail validée de umassmemorial.org
Jun XuProfessor, Nanjing University of Information Science & Technology, ChinaAdresse e-mail validée de case.edu
German CorredorEmory UniversityAdresse e-mail validée de emory.edu
Cheng LuGuangdong Provincial People's Hospital, Southern Medical UniversityAdresse e-mail validée de gdph.org.cn
Patrick LeoGenentechAdresse e-mail validée de gene.com
Robert TothRutgers UniversityAdresse e-mail validée de eden.rutgers.edu

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Anant Madabhushi

Department of Biomedical Engineering, Professor, Biomedical Engineering, Emory Univ & Georgia Tech

Adresse e-mail validée de emory.edu

computational pathology biomedical image analysis digital pathology data fusion cancer imaging


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	1984	2009
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	1287	2019
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases A Janowczyk, A Madabhushi Journal of pathology informatics 7 (1), 29, 2016	1082	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	870	2015
Image analysis and machine learning in digital pathology: Challenges and opportunities A Madabhushi, G Lee Medical image analysis 33, 170-175, 2016	738	2016
Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology K Bera, KA Schalper, DL Rimm, V Velcheti, A Madabhushi Nature reviews Clinical oncology 16 (11), 703-715, 2019	720	2019
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	612	2014
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	602	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 … D Stoyanov, Z Taylor, G Carneiro, T Syeda-Mahmood, A Martel, ... Springer, 2018	489	2018
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	478	2016
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	470	2013
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	454	2015
A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection AA Cruz-Roa, JE Arevalo Ovalle, A Madabhushi, FA González Osorio Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013	449	2013
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 (1), 1-14, 2017	444	2017
Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI NM Braman, M Etesami, P Prasanna, C Dubchuk, H Gilmore, P Tiwari, ... Breast Cancer Research 19 (1), 1-14, 2017	441	2017
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	424	2008
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	388	2003
Radiomics and radiogenomics in lung cancer: a review for the clinician R Thawani, M McLane, N Beig, S Ghose, P Prasanna, V Velcheti, ... Lung cancer 115, 34-41, 2018	381	2018
Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features H Wang, A Cruz-Roa, A Basavanhally, H Gilmore, N Shih, M Feldman, ... Journal of Medical Imaging 1 (3), 034003-034003, 2014	364	2014
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	362	2008

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