| Supervised multi-view canonical correlation analysis (sMVCCA): Integrating histologic and proteomic features for predicting recurrent prostate cancer G Lee, A Singanamalli, H Wang, MD Feldman, SR Master, NNC Shih, ... IEEE transactions on medical imaging 34 (1), 284-297, 2014 | 114 | 2014 |
| Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings G Penzias, A Singanamalli, R Elliott, J Gollamudi, N Shih, M Feldman, ... PloS one 13 (8), e0200730, 2018 | 63 | 2018 |
| Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer A Singanamalli, M Rusu, RE Sparks, NNC Shih, A Ziober, LP Wang, ... Journal of Magnetic Resonance Imaging 43 (1), 149-158, 2016 | 45 | 2016 |
| Cascaded multi-view canonical correlation (CaMCCo) for early diagnosis of Alzheimer’s disease via fusion of clinical, imaging and omic features A Singanamalli, H Wang, A Madabhushi Scientific reports 7 (1), 8137, 2017 | 27 | 2017 |
| Supervised multi-view canonical correlation analysis: Fused multimodal prediction of disease diagnosis and prognosis A Singanamalli, H Wang, G Lee, N Shih, M Rosen, S Master, ... Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and …, 2014 | 14 | 2014 |
| AutoStitcher: An automated program for efficient and robust reconstruction of digitized whole histological sections from tissue fragments G Penzias, A Janowczyk, A Singanamalli, M Rusu, N Shih, M Feldman, ... Scientific Reports 6 (1), 29906, 2016 | 13 | 2016 |
| Identifying in vivo DCE MRI parameters correlated with ex vivo quantitative microvessel architecture: A radiohistomorphometric approach A Singanamalli, R Sparks, M Rusu, N Shih, A Ziober, J Tomaszewski, ... Medical Imaging 2013: Digital Pathology 8676, 37-50, 2013 | 8 | 2013 |
| Improved automated segmentation of human kidney organoids using deep convolutional neural networks M MacDonald, TR Fennel, A Singanamalli, NM Cruz, M Yousefhussein, ... Medical Imaging 2020: Image Processing 11313, 832-839, 2020 | 5 | 2020 |
| Selecting features with group-sparse nonnegative supervised canonical correlation analysis: multimodal prostate cancer prognosis H Wang, A Singanamalli, S Ginsburg, A Madabhushi Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 3 | 2014 |
| Blood flow anomaly detection via generative adversarial networks: a preliminary study A Singanamalli, J Mitra, K Wallace, P Venugopal, S Smith, L Mo, ... Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and …, 2020 | 2 | 2020 |
| Improved noninvasive prostate cancer assessment using multiparametric magnetic resonance imaging X Li, A Singanamalli, D Shanbhag, AM Hötker, O Aras, O Akin, R Bhagalia 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1199-1203, 2016 | 2 | 2016 |
| Techniques for determining ultrasound probe motion PW Lorraine, DA Shoudy, A Singanamalli US Patent 11,911,213, 2024 | 1 | 2024 |
| Systems and methods for image classification Y Al-Kofahi, M MacDonald, A Singanamalli, M Yousefhussien, W Marshall US Patent 11,798,270, 2023 | 1 | 2023 |
| Delivery of therapeutic neuromodulation A Singanamalli, DA Shoudy, JM Ashe, CM Puleo US Patent 11,602,331, 2023 | 1 | 2023 |
| Systems and methods for image classification Y Al-Kofahi, M MacDonald, A Singanamalli, M Yousefhussien, W Marshall US Patent App. 18/470,823, 2024 | | 2024 |
| Delivery of therapeutic neuromodulation A Singanamalli, DA Shoudy, JM Ashe, CM Puleo US Patent App. 18/179,834, 2023 | | 2023 |
| Automated detection and localization of bleeding J Mitra, L Marinelli, A Singanamalli US Patent 11,583,188, 2023 | | 2023 |
| Impact of tissue image segmentation errors on SAR A Singanamalli, M Tarasek, Q Liu, D Yeo, T Foo Proc. Intl. Soc. Mag. Reson. Med 26, 1466, 2018 | | 2018 |
| Identifying the Histomorphometric Basis of MRI Radiomic Features in Distinguishing Gleason Grades of Prostate Cancer G Penzias, A Singanamalli, R Elliott, J Gollamudi, N Shih, M Feldman, ... LABORATORY INVESTIGATION 97, 400A-401A, 2017 | | 2017 |
| AutoStitcherTM: An Automated Program for Accurate Reconstruction of Digitized Whole Histological Sections From Tissue Fragments G Penzias, A Janowczyk, A Singanamalli, M Rusu, N Shih, M Feldman, ... MODERN PATHOLOGY 28, 400A-401A, 2015 | | 2015 |
