Michael Feldman | Case School of Engineering

Patents Received

2012, "Malignancy diagnosis using content-based image retreival of tissue histopathology" EP2174263 A1, Anant Madabhushi, Scott Doyle, Michael Feldman, & John Tomaszewski.

2012, "Computer Assisted Diagnosis (CAD) of cancer using Multi-Functional Multi-Modal in vivo Magnetic Resonance Spectroscopy (MRS) and Imaging (MRI)" 8,295,575, Pallavi Tiwari, Anant Madabhushi, Satish Viswanath, Robert Toth, Michael Feldman, John Tomaszewski, & Mark Rosen.

2012, "Computer Assisted Diagnosis (CAD) of cancer using Multi-Functional Multi-Modal in vivo Magnetic Resonance Spectroscopy (MRS) and Imaging (MRI)" US 8295575 B2, Anant Madabhushi, Michael Feldman, John Tomaszewski, Mark Rosen, Satish Viswanath, Pallavi Tiwari, & Robert Toth.

2012, "Systems and methods for classification of biological datasets" 8204315, Anant Madabhushi, Michael Feldman, John Tomaszewski, Mark Rosen, & Jianbo Shi.

Patents Pending

2009, "System and Method for Accurate and Rapid Identification of Diseased Regions on Biological Images with Applications to Disease Diagnosis and Prognosis" US 2011/0243417 A1, Anant Madabhushi, James Monaco, Michael Feldman, John Tomaszewski, & Ajay Basavanhally.

Publications

Peyster, E., Arabyarmohammadi , S., Janowczyk, A., Azarianpour-Esfahani, S., Sekulic, M., Cassol, C., Blower, L., Parwani, A., Lal, P., Feldman, M., Margulies, K., & Madabhushi, A. (2021). An automated computational image analysis pipeline for histological grading of cardiac allograft rejection. European Heart Journal, 42 (24), 2356-2369.

Leo, P., Janowczyk, A., Elliott, R., Janaki, N., Bera, K., Shiradkar, R., Farre, X., Fu, P., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T., Khani, F., Robinson, B., Eklund, L., Jambor, I., Merisaari, H., , O., Taimen, P., Aronen, H., Boström, P., Tewari, A., Magi-Galluzzi, C., Klein, E., Purysko, A., Shin, N., Feldman, M., Gupta, S., Lai, P., & Madabhushi, A. (2021). Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study. NPJ Precision Oncology, 5 (1), 35.

Leo, P., Chandramouli, S., Farre, X., Elliott, R., Janowczyk, A., Bera, K., Fu, P., Janaki, N., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T., Khani, F., Robinson, B., Shih, N., Feldman, M., Gupta, S., McKenney, J., Lai, P., & Madabhushi, A. (2021). Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. European Urology Focus.

Li, H., Bera, K., Toro, P., Fu, P., Zhang, Z., Lu, C., Feldman, M., Ganesan, S., Goldstein, L., Davidson, N., & Others, N. (2021). Collagen fiber orientation disorder from H\&E images is prognostic for early stage breast cancer: clinical trial validation. npj Breast Cancer, 7 (1), 1--10.

Bhargava, H., Leo, P., Elliott, R., Janowczyk, A., Whitney, J., Gupta, S., Fu, P., Yamoah, K., Khani, F., Robinson, B., Rebbeck, T., Feldman, M., Lal, P., & Madabhushi, A. (2020). Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients. Clinical Cancer Research, 26 (8), 1915-1923.

Bhargava, H., Leo, P., Elliott, R., Janowczyk, A., Whitney, J., Gupta, S., Fu, P., Yamoah, K., Khani, F., Robinson, B., Rebbeck, T., Feldman, M., Lal, P., & Madabhushi, A. (2020). Computationally derived image signature of stromal morphology is prognostic of prostate cancer recurrence following prostatectomy in African American patients. Clinical Cancer Research, 26 (8), 1915-1923.

Leo, P., Elliott, R., Janowczyk, A., Janaki, N., Bera, K., Shiradkar, R., El-Fahmawi, A., Kim, J., Shahait, M., Shah, A., Thulasidass, H., Tewari, A., Gupta, S., Shih, N., Feldman, M., Lal, P., Lee, D., & Madabhushi, A. (2020). PD52-02 COMPUTER-EXTRACTED FEATURES OF GLAND MORPHOLOGY FROM DIGITAL TISSUE IMAGES IS COMPARABLE TO DECIPHER FOR PROGNOSIS OF BIOCHEMICAL RECURRENCE RISK POST-SURGERY. The Journal of Urology, 203 , e1089-e1090.

Khorrami, M., Prasanna, P., Gupta, A., Patil, P., Velu, P., Thawani, R., Corredor-Prada, G., Alilou, M., Bera, K., Fu, P., Feldman, M., Velcheti, V., & Madabhushi, A. (2020). Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in NonSmall Cell Lung Cancer. Cancer Immunology Research, 8 (1), 108-119.

Janowczyk, A., Zuo, R., Gilmore, H., Feldman, M., & Madabhushi, A. (2019). HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides. JCO Clinical Cancer Informatics.

Janowczyk, A., Zuo, R., Gilmore, H., Feldman, M., & Madabhushi, A. (2019). HistoQC: An open-source quality control tool for digital pathology slides. JCO Clinical Cancer Informatics, 3

Leo, P., Elliott, R., Shih, N., Gupta, S., Feldman, M., & Madabhushi, A. (2018). Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study. Scientific Reports, 8 (1).

Whitney, J., Corredor-Prada, G., Janowczyk, A., Ganesan, S., Doyle, S., Tomaszewski, J., Feldman, M., Gilmore, H., & Madabhushi, A. (2018). Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer. BMC Cancer, 18 (1).

Penzias, G., Singanamalli, A., Elliott, R., Gollamudi, J., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., B�hm, M., Haynes, A., Ponsky, L., Fu, P., Tiwari, P., Viswanath, S. E., & Madabhushi, A. E. (2018). Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings. PLoS ONE, 13 (8).

Cruz-Roa, A., Gilmore, H., Basavanhally, A., Feldman, M., Ganesan, S., Shih, N., Tomaszewski, J., Madabhushi, A., & Gonz�lez, F. (2018). High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection. PLoS ONE, 13 (5).

Leo, P., Gawlik, A., Zhu, G., Feldman, M., Gupta, S., Veltri, R., & Madabhushi, A. (2018). MP35-02 COMPUTER-EXTRACTED FEATURES OF NUCLEAR AND GLANDULAR MORPHOLOGY FROM DIGITAL H&E TISSUE IMAGES PREDICT PROSTATE CANCER BIOCHEMICAL RECURRENCE AND METASTASIS FOLLOWING RADICAL PROSTATECTOMY. The Journal of Urology, 199 (4), e446-e447.

Nirschl, J., Janowczyk, A., Peyster, E., Frank, R., Margulies, K., Feldman, M., & Madabhushi, A. (2018). A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H and e tissue. PLoS ONE, 13 (4).

Whitney, J., Romeo-Bucheli, D., Janowczyk, A., Ganesan, S., Feldman, M., Gilmore, H., & Madabhushi, A. (2018). Abstract P4-09-11: Computer extracted features of tumor grade from H&E images predict oncotype DX risk categories for early stage ER+ breast cancer. Cancer Research, 78 (4 Supplement), P4-09-11-P4-09-11.

Ghose, S., Shiradkar, R., Rusu, M., Mitra, J., Thawani, R., Feldman, M., Gupta, A., Purysko, A., Ponsky, L., & Madabhushi, A. (2017). Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings. Scientific Reports, 7 (1).

De Leon, A., Lee, G., Shih, N., Elliott, R., Feldman, M., & Madabhushi, A. (2016). Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.. Journal of medical imaging (Bellingham, Wash.), 3 (4), 047502.

Penzias, G., Janowczyk, A., Singanamalli, A., Rusu, M., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., Böhm, M., Haynes, A., Ponsky, L., Viswanath, S. E., & Madabhushi, A. E. (2016). AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments. Scientific Reports, 6

Litjens, G., Elliott, R., Shih, N., Feldman, M., Kobus, T., De Hulsbergen-van Kaa, C., Barentsz, J., Huisman, H., & Madabhushi, A. (2016). Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging.. Radiology, 278 (1), 135-45.

Singanamalli, A., Rusu, M., Sparks, R., Shih, N., Ziober, A., Wang, Y., Tomaszewski, J., Rosen, M., Feldman, M., & Madabhushi, A. (2016). Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer.. Journal of magnetic resonance imaging : JMRI, 43 (1), 149-58.

Xu, J., Xiang, L., Wang, P., Ganesan, S., Feldman, M., Shih, N., Gilmore, H., & Madabhushi, A. (2015). Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 46 Pt 1 , 20-9.

Lee, G., Singanamalli, A., Wang, Z., Feldman, M., Master, S., Shih, N., Spangler, E., Rebbeck, T., Tomaszewski, J., & Madabhushi, A. (2015). Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancer.. IEEE transactions on medical imaging, 34 (1), 284-97.

Madabhushi, A., Cruz-Rao, A., Basanvanhally, A., Gilmore, H., Shih, N., Feldman, M., Tomaszewski, J., & Gonzalez, F. (2014). Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features. Journal of Medical Imaging, 1 (3), 13 pages.

Wang, Z., Cruz-Roa, A., Basavanhally, A., Gilmore, H., Shih, N., Feldman, M., Tomaszewski, J., Gonzalez, F., & Madabhushi, A. (2014). Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.. Journal of medical imaging (Bellingham, Wash.), 1 (3), 034003.

Madabhushi, A., Litjens, G., Huisman, H., Elliott, R., Shin, N., Feldman, M., Viswanath, S. E., Futterer, J. E., & Bomers, J. E. (2014). Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy. Journal of Medical Imaging, 1 (3), 9 pages.

Litjens, G., Huisman, H., Elliott, R., Shih, N., Feldman, M., Viswanath, S. E., Futterer, J. E., Bomers, J. E., & Madabhushi, A. E. (2014). Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy.. Journal of medical imaging (Bellingham, Wash.), 1 (3), 035001.

Litjens, G., Huisman, H., Elliott, R., Shih, N., Feldman, M., Viswanath, S. E., Futterer, J. E., Bomers, J. E., & Madabhushi, A. E. (2014). Quantitative identification of MRI features of prostate cancer response following laser ablation and radical prostatectomy. Journal of Medical Imaging.

Agner, S., Rosen, M., Englander, S., Tomaszewski, J., Feldman, M., Zhang, P., Miesner, C., Schnall, M., & Madabhushi, A. (2014). Computerized image analysis for identifying triple-negative breast cancers and differentiating them from other molecular subtypes of breast cancer on dynamic contrast-enhanced MR images: a feasibility study.. Radiology, 272 (1), 91-9.

Lee, G., Sparks, R., Karabalin, R., Shih, N., Feldman, M., Spangler, E., Rebbeck, T., Tomaszewski, J., & Madabhushi, A. (2014). Co-occurring gland angularity in localized subgraphs: predicting biochemical recurrence in intermediate-risk prostate cancer patients.. PloS one, 9 (5), e97954.

Toth, R., Shih, N., Tomaszewski, J., Feldman, M., Kutter, O., Cymbalyuk, G., Paulus, Jr, J., Paladini, G., & Madabhushi, A. (2014). Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework.. Journal of pathology informatics, 5 (1), 8.

Agner, S., Rosen, M., Englander, S., Tomaszewski, J., Feldman, M., Zhang, P., Miesner, C., Schnall, M., & Madabhushi, A. (2014). Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study.. Radiology.

Basavanhally, A., Ganesan, S., Feldman, M., Shih, N., Miesner, C., Tomaszewski, J., & Madabhushi, A. (2013). Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides.. IEEE transactions on bio-medical engineering, 60 (8), 2089-99.

Ghaznavi, F., Evans, A., Madabhushi, A., & Feldman, M. (2013). Digital imaging in pathology: whole-slide imaging and beyond.. Annual review of pathology, 8 , 331-59.

Doyle, S., Feldman, M., Shih, N., Tomaszewski, J., & Madabhushi, A. (2012). Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer.. BMC bioinformatics, 13 , 282.

Janowczyk, A., Chandran, S., Singh, U., Sasaroli, D., Coukos, G., Feldman, M., & Madabhushi, A. (2012). High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts.. IEEE transactions on bio-medical engineering, 59 (5), 1240-52.

Doyle, S., Feldman, M., Tomaszewski, J., & Madabhushi, A. (2012). A boosted Bayesian multiresolution classifier for prostate cancer detection from digitized needle biopsies.. IEEE transactions on bio-medical engineering, 59 (5), 1205-18.

Hipp, J., Monaco, J., Kunju, L., Cheng, J., Yagi, Y., Rodriguez-Canales, J., Emmert-Buck, M., Hewitt, S., Feldman, M., Tomaszewski, J., Toner, M., Tompkins, R., Flotte, T., Lucas, D., Gilbertson, J., Madabhushi, A., & Balis, U. (2012). Integration of architectural and cytologic driven image algorithms for prostate adenocarcinoma identification.. Analytical cellular pathology (Amsterdam), 35 (4), 251-65.

Golugula, A., Lee, G., Master, S., Feldman, M., Tomaszewski, J., Speicher, D., & Madabhushi, A. (2011). Supervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery.. BMC bioinformatics, 12 , 483.

Doyle, S., Monaco, J., Feldman, M., Tomaszewski, J., & Madabhushi, A. (2011). An active learning based classification strategy for the minority class problem: application to histopathology annotation.. BMC bioinformatics, 12 , 424.

Xiao, G., Bloch, B., Chappelow, J., Genega, E., Rofsky, N., Lenkinski, R., Tomaszewski, J., Feldman, M., Rosen, M., & Madabhushi, A. (2011). Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 35 (7-8), 568-78.

Chappelow, J., Tomaszewski, J., Feldman, M., Shih, N., & Madabhushi, A. (2011). HistoStitcher(©): an interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 35 (7-8), 557-67.

Yu, S., Monaco, J., Tomaszewski, J., Shih, N., Feldman, M., & Madabhushi, A. (2011). Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 3427-30.

Patel, P., Chappelow, J., Tomaszewski, J., Feldman, M., Rosen, M., Shih, N., & Madabhushi, A. (2011). Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 6269-72.

Golugula, A., Lee, G., Master, S., Feldman, M., Tomaszewski, J., & Madabhushi, A. (2011). Supervised regularized canonical correlation analysis: integrating histologic and proteomic data for predicting biochemical failures.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 6434-7.

Hipp, J., Cheng, J., Pantanowitz, L., Hewitt, S., Yagi, Y., Monaco, J., Madabhushi, A., Rodriguez-Canales, J., Hanson, J., Roy-Chowdhuri, S., Filie, A., Feldman, M., Tomaszewski, J., Shih, N., Brodsky, V., Giaccone, G., Emmert-Buck, M., & Balis, U. (2011). Image microarrays (IMA): Digital pathology's missing tool.. Journal of pathology informatics, 2 , 47.

Basavanhally, A., Feldman, M., Shih, N., Miesner, C., Tomaszewski, J., Ganesan, S., & Madabhushi, A. (2011). Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX.. Journal of pathology informatics, 2 , S1.

Monaco, J., Tomaszewski, J., Feldman, M., Hagemann, I., Moradi, M., Mousavi, P., Boag, A., Davidson, C., Abolmaesumi, P., & Madabhushi, A. (2010). High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models.. Medical image analysis, 14 (4), 617-29.

Madabhushi, A., Doyle, S., Lee, G., Basavanhally, A., Monaco, J., Masters, S., Tomaszewski, J., & Feldman, M. (2010). Integrated diagnostics: a conceptual framework with examples.. Clinical chemistry and laboratory medicine, 48 (7), 989-98.

Fatakdawala, H., Xu, J., Basavanhally, A., Bhanot, G., Ganesan, S., Feldman, M., Tomaszewski, J., & Madabhushi, A. (2010). Expectation-maximization-driven geodesic active contour with overlap resolution (EMaGACOR): application to lymphocyte segmentation on breast cancer histopathology.. IEEE transactions on bio-medical engineering, 57 (7), 1676-89.

Basavanhally, A., Ganesan, S., Agner, S., Monaco, J., Feldman, M., Tomaszewski, J., Bhanot, G., & Madabhushi, A. (2010). Computerized image-based detection and grading of lymphocytic infiltration in HER2+ breast cancer histopathology.. IEEE transactions on bio-medical engineering, 57 (3), 642-53.

Janowczyk, A., Chandran, S., Singh, U., Sasaroli, D., Coukos, G., Feldman, M., & Madabhushi, A. (2009). Hierarchical normalized cuts: unsupervised segmentation of vascular biomarkers from ovarian cancer tissue microarrays.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 12 (Pt 1), 230-8.

Doyle, S., Rodriguez, C., Madabhushi, A., Tomaszeweski, J., & Feldman, M. (2006). Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 1 , 4759-62.

Doyle, S., Madabhushi, A., Feldman, M., & Tomaszeweski, J. (2006). A boosting cascade for automated detection of prostate cancer from digitized histology.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 9 (Pt 2), 504-11.

Madabhushi, A., Feldman, M., Metaxas, D., Tomaszeweski, J., & Chute, D. (2005). Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI.. IEEE transactions on medical imaging, 24 (12), 1611-25.

Madabhushi, A., Shi, J., Rosen, M., Tomaszeweski, J., & Feldman, M. (2005). Graph embedding to improve supervised classification and novel class detection: application to prostate cancer.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 8 (Pt 1), 729-37.