Deep Learning based NAS Score and Fibrosis Stage Prediction from CT and Pathology Data
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Dimitris N. Metaxas | Hui Qu | Ananya Jana | Dimitris Metaxas | Puru Rattan | Carlos D. Minacapelli | Vinod Rustgi | Carlos D Minacapelli | Hui Qu | V. Rustgi | Ananya Jana | Puru Rattan
[1] Pierre Bedossa,et al. Pathology of non‐alcoholic fatty liver disease , 2017, Liver international : official journal of the International Association for the Study of the Liver.
[2] Richard L. Ehman,et al. Non-invasive detection of liver fibrosis: MR imaging features vs. MR elastography , 2015, Abdominal Imaging.
[3] Tong Liu,et al. Segmentation of histological images and fibrosis identification with a convolutional neural network , 2018, Comput. Biol. Medicine.
[4] G. Birk,et al. Deep learning enables pathologist-like scoring of NASH models , 2019, Scientific Reports.
[5] P. Kamath,et al. Burden of liver diseases in the world. , 2019, Journal of hepatology.
[6] Jin-Young Choi,et al. Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver. , 2018, Radiology.
[7] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[8] B. Bolster,et al. Accuracy of MR elastography and anatomic MR imaging features in the diagnosis of severe hepatic fibrosis and cirrhosis , 2012, Journal of magnetic resonance imaging : JMRI.
[9] Hanry Yu,et al. Deep learning enables automated scoring of liver fibrosis stages , 2018, Scientific Reports.
[10] Albert Montillo,et al. Deep learning convolutional neural networks for the estimation of liver fibrosis severity from ultrasound texture , 2019, Medical Imaging.
[11] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[12] O. Abe,et al. Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid-enhanced Hepatobiliary Phase MR Images. , 2017, Radiology.
[13] P. Giral,et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. , 2005, Gastroenterology.
[14] Ilias Gatos,et al. Temporal stability assessment in shear wave elasticity images validated by deep learning neural network for chronic liver disease fibrosis stage assessment. , 2019, Medical physics.
[15] A. Huber,et al. CT predicts liver fibrosis: Prospective evaluation of morphology- and attenuation-based quantitative scores in routine portal venous abdominal scans , 2018, PloS one.
[16] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] O. Abe,et al. Deep learning for staging liver fibrosis on CT: a pilot study , 2018, European Radiology.
[19] A. Cardona,et al. An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy , 2010, PLoS biology.
[20] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[21] S. Alavian,et al. Inter-observer and Intra-observer Agreement in Pathological Evaluation of Non-alcoholic Fatty Liver Disease Suspected Liver Biopsies , 2014, Hepatitis monthly.
[22] Michael Charlton,et al. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases , 2018, Hepatology.