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Pina C. Sanelli
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2020 – today
- 2024
- [j7]Tran Anh Tuan
, Tal Ze'evi
Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan. npj Digit. Medicine 7(1) (2024) - 2021
- [c7]Nguyen P. Nguyen, Youngjin Yoo, Andrei Chekkoury, Eva Eibenberger, Thomas J. Re, Jyotipriya Das, Abishek Balachandran, Yvonne W. Lui, Pina C. Sanelli, Thomas J. Schroeppel, Uttam Bodanapally, Savvas Nicolaou, Tommi A. White, Filiz Bunyak
Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans. ICCVW 2021: 487-495 - 2020
- [i2]Shikha Chaganti, Abishek Balachandran, Guillaume Chabin, Stuart Cohen, Thomas Flohr, Bogdan Georgescu, Philippe Grenier, Sasa Grbic, Siqi Liu, François Mellot, Nicolas Murray, Savvas Nicolaou, William Parker, Thomas J. Re, Pina C. Sanelli, Alexander W. Sauter, Zhoubing Xu, Youngjin Yoo, Valentin Ziebandt, Dorin Comaniciu:
Quantification of Tomographic Patterns associated with COVID-19 from Chest CT. CoRR abs/2004.01279 (2020) - [i1]Bogdan Georgescu, Shikha Chaganti, Gorka Bastarrika Aleman, Eduardo Jose Mortani Barbosa Jr., Jordi Broncano Cabrero, Guillaume Chabin, Thomas Flohr, Philippe Grenier, Sasa Grbic, Nakul Gupta, François Mellot, Savvas Nicolaou, Thomas J. Re, Pina C. Sanelli, Alexander W. Sauter, Youngjin Yoo, Valentin Ziebandt, Dorin Comaniciu:
Machine Learning Automatically Detects COVID-19 using Chest CTs in a Large Multicenter Cohort. CoRR abs/2006.04998 (2020)
2010 – 2019
- 2019
- [j6]Peng Liu
Deep Evolutionary Networks with Expedited Genetic Algorithms for Medical Image Denoising. Medical Image Anal. 54: 306-315 (2019) - [p1]Yao Xiao, Skylar E. Stolte
Deep Spatial-Temporal Convolutional Neural Networks for Medical Image Restoration. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics 2019: 261-275 - 2017
- [j5]Ruogu Fang
TENDER: Tensor non-local deconvolution enabled radiation reduction in CT perfusion. Neurocomputing 229: 13-22 (2017) - [c6]Yao Xiao, Ajay Gupta, Pina C. Sanelli, Ruogu Fang
STAR: Spatio-Temporal Architecture for Super-Resolution in Low-Dose CT Perfusion. MLMI@MICCAI 2017: 97-105 - 2016
- [c5]Ruogu Fang
Direct estimation of permeability maps for low-dose CT perfusion. ISBI 2016: 739-742 - 2015
- [j4]Ruogu Fang
Sparsity techniques in medical imaging. Comput. Medical Imaging Graph. 46: 1 (2015) - [j3]Ruogu Fang
Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization. IEEE Trans. Medical Imaging 34(7): 1533-1548 (2015) - 2014
- [j2]Ruogu Fang
Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model. Medical Image Anal. 18(6): 866-880 (2014) - [c4]Ruogu Fang
Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion. MICCAI (1) 2014: 154-161 - 2013
- [j1]Ruogu Fang
Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning. Medical Image Anal. 17(4): 417-428 (2013) - [c3]Ruogu Fang
Tissue-Specific Sparse Deconvolution for Low-Dose CT Perfusion. MICCAI (1) 2013: 114-121 - 2012
- [c2]Ruogu Fang
Sparsity-based deconvolution of low-dose brain perfusion CT in subarachnoid hemorrhage patients. ISBI 2012: 872-875 - [c1]Ruogu Fang
Sparsity-Based Deconvolution of Low-Dose Perfusion CT Using Learned Dictionaries. MICCAI (1) 2012: 272-280
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