Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach. - Asha Singanamalli; Rachel Sparks; Mirabela Rusu; Natalie Shih; Amy Ziober; John Tomaszewski 001; Mark Rosen; Michael D. Feldman; Anant Madabhushi (Digital Pathology, 2013)

Selecting Features with Group-Sparse Nonnegative Supervised Canonical Correlation Analysis: Multimodal Prostate Cancer Prognosis. - Haibo Wang; Asha Singanamalli; Shoshana Ginsburg; Anant Madabhushi (MICCAI (3), 2014)

Supervised Multi-View Canonical Correlation Analysis (sMVCCA): Integrating Histologic and Proteomic Features for Predicting Recurrent Prostate Cancer. - George Lee 002; Asha Singanamalli; Haibo Wang; Michael D. Feldman; Stephen R. Master; Natalie N. C. Shih; Elaine Spangler; Timothy R. Rebbeck; John Tomaszewski 001; Anant Madabhushi (IEEE Trans. Medical Imaging, 2015)

Improved noninvasive prostate cancer assessment using multiparametric magnetic resonance imaging. - Xia Li; Asha Singanamalli; Dattesh Shanbhag; Andreas M. Hötker; Omer Aras; Oguz Akin; Roshni Bhagalia (ISBI, 2016)

Blood flow anomaly detection via generative adversarial networks: a preliminary study. - Asha Singanamalli; Jhimli Mitra; Kirk Wallace; Prem Venugopal; Scott Smith; Larry Mo; Lai Yee Leung; Jonathan Morrison; Todd Rasmussen; Luca Marinelli (Image-Guided Procedures, 2020)

Improved automated segmentation of human kidney organoids using deep convolutional neural networks. - Michael MacDonald; Theron R. Fennel; Asha Singanamalli; Nelly M. Cruz; Mohammad Yousefhussein; Yousef Al-Kofahi; Benjamin S. Freedman (Image Processing, 2020)