Natalie Shih - RankMe

15 papers B 1Journal 3Unranked 11

Year	Rank	Type	Title / Venue / Authors
2014	—	`conf`	Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. Digital Pathology Angel Cruz-Roa, Ajay Basavanhally, Fabio A. González, Hannah Gilmore, Michael D. Feldman, Shridar Ganesan, Natalie Shih, John Tomaszewski, Anant Madabhushi
2014	—	`conf`	Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection. Digital Pathology Haibo Wang, Angel Cruz-Roa, Ajay Basavanhally, Hannah Gilmore, Natalie Shih, Mike Feldman, John Tomaszewski, Fabio A. González, Anant Madabhushi
2014	—	`conf`	Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation. Image-Guided Procedures Geert Litjens, Henkjan J. Huisman, R. Elliott, Natalie Shih, Michael D. Feldman, Satish Viswanath, Jurgen J. Fütterer, J. Bomers, Anant Madabhushi
2014	—	`conf`	Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI. Computer-Aided Diagnosis Geert J. S. Litjens, R. Elliott, Natalie Shih, Michael D. Feldman, Jelle O. Barentsz, Christina A. Hulsbergen van de Kaa, Iringo Kovacs, Henkjan J. Huisman, Anant Madabhushi
2014	B	`conf`	Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI. Image Processing Eileen Hwuang, Mirabela Rusu, Sudha Karthigeyan, Shannon Agner, Rachel Sparks, Natalie Shih, John Tomaszewski, Mark Rosen, Michael D. Feldman, Anant Madabhushi
2013	—	`conf`	Co-occurring gland tensors in localized cluster graphs: Quantitative histomorphometry for predicting biochemical recurrence for intermediate grade prostate cancer. ISBI George Lee, Rachel Sparks, Sahirzeeshan Ali, Anant Madabhushi, Michael D. Feldman, Stephen R. Master, Natalie Shih, John Tomaszewski
2013	—	`conf`	Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach. Digital Pathology Asha Singanamalli, Rachel Sparks, Mirabela Rusu, Natalie Shih, Amy Ziober, John Tomaszewski, Mark Rosen, Michael D. Feldman, Anant Madabhushi
2013	J	`jnl`	Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides. IEEE Trans. Biomed. Eng. Ajay Basavanhally, Shridar Ganesan, Michael D. Feldman, Natalie Shih, Carolyn Mies, John Tomaszewski, Anant Madabhushi
2012	J	`jnl`	Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. BMC Bioinform. Scott Doyle, Michael D. Feldman, Natalie Shih, John Tomaszewski, Anant Madabhushi
2012	—	`conf`	Incorporating the whole-mount prostate histology reconstruction program Histostitcher into the extensible imaging platform (XIP) framework. Computer-Aided Diagnosis Robert Toth, Jonathan Chappelow, Christoph Vetter, Oliver Kutter, Christoph Russ, Michael D. Feldman, John Tomaszewski, Natalie Shih, Anant Madabhushi
2011	—	`conf`	A boosted classifier for integrating multiple fields of view: Breast cancer grading in histopathology. ISBI Ajay Basavanhally, Shridar Ganesan, Natalie Shih, Carolyn Mies, Michael D. Feldman, John Tomaszewski, Anant Madabhushi
2011	—	`conf`	Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology. ISBI Scott Doyle, Michael D. Feldman, John Tomaszewski, Natalie Shih, Anant Madabhushi
2011	—	`conf`	Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models. EMBC Elaine Yu, James P. Monaco, John Tomaszewski, Natalie Shih, Michael D. Feldman, Anant Madabhushi
2011	J	`jnl`	HistoStitcher Comput. Medical Imaging Graph. Jonathan Chappelow, John Tomaszewski, Michael D. Feldman, Natalie Shih, Anant Madabhushi
2011	—	`conf`	Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI. EMBC Pratik Patel, Jonathan Chappelow, John Tomaszewski, Michael D. Feldman, Mark Rosen, Natalie Shih, Anant Madabhushi