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Deep Learning Prediction of Voxel-Level Liver Stiffness in Patients with Nonalcoholic Fatty Liver Disease

https://doi.org/10.1148/ryai.2021200274
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/hep.28431openalex-snapshot
Global epidemiology of nonalcoholic fatty liver disease—Meta‐analytic assessment of prevalence, incidence, and outcomes
inferredcites →https://doi.org/10.1002/jmri.25550openalex-snapshot
Liver fibrosis: Review of current imaging and MRI quantification techniques
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-snapshot
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/s00330-015-3949-zopenalex-snapshot
Magnetic resonance elastography for staging liver fibrosis in non-alcoholic fatty liver disease: a diagnostic accuracy systematic review and individual participant data pooled analysis
inferredcites →https://doi.org/10.1007/s00330-018-5680-zopenalex-snapshot
Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis
inferredcites →https://doi.org/10.1007/s00330-020-06831-8openalex-snapshot
Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology
inferredcites →https://doi.org/10.1016/s1361-8415(00)00039-6openalex-snapshot
Magnetic resonance elastography: Non-invasive mapping of tissue elasticity
inferredcites →https://doi.org/10.1056/nejm200102153440706openalex-snapshot
Liver Biopsy
inferredcites →https://doi.org/10.1056/nejmra011775openalex-snapshot
Nonalcoholic Fatty Liver Disease
inferredcites →https://doi.org/10.1056/nejmra1610570openalex-snapshot
Use of Liver Imaging and Biopsy in Clinical Practice
inferredcites →https://doi.org/10.1111/liv.13643openalex-snapshot
Global epidemiology of non‐alcoholic fatty liver disease/non‐alcoholic steatohepatitis: What we need in the future
inferredcites →https://doi.org/10.1126/science.7569924openalex-snapshot
Magnetic Resonance Elastography by Direct Visualization of Propagating Acoustic Strain Waves
inferredcites →https://doi.org/10.1148/radiol.2015142141openalex-snapshot
Hepatic MR Elastography: Clinical Performance in a Series of 1377 Consecutive Examinations
inferredcites →https://doi.org/10.1148/radiol.2017171928openalex-snapshot
Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid–enhanced Hepatobiliary Phase MR Images
inferredcites →https://doi.org/10.1148/radiol.2018180763openalex-snapshot
Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent–enhanced CT Images in the Liver
inferredcites →https://doi.org/10.21105/joss.01026openalex-snapshot
Pingouin: statistics in Python
inferredcites →https://doi.org/10.2214/ajr.19.21082openalex-snapshot
Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data
inferredcites →https://doi.org/10.2214/ajr.19.21267openalex-snapshot
Comparison of 2D Shear Wave Elastography, Transient Elastography, and MR Elastography for the Diagnosis of Fibrosis in Patients With Nonalcoholic Fatty Liver Disease

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.5245657openalex-extracted
Mechanical Characterization of Brain Tissue: Experimental Techniques, Human Testing Considerations, and Perspectives
inferred← citeshttps://doi.org/10.1002/ird3.24openalex-snapshot
Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases
inferred← citeshttps://doi.org/10.1002/ird3.70045openalex-snapshot
Virtual Magnetic Resonance Elastography Using a Deep Generative Model for Liver Fibrosis Staging
inferred← citeshttps://doi.org/10.1007/978-3-031-43999-5_32openalex-snapshot
Physics-Informed Neural Networks for Tissue Elasticity Reconstruction in Magnetic Resonance Elastography
inferred← citeshttps://doi.org/10.1007/s00261-025-05160-yopenalex-snapshot
Advanced liver fibrosis detection using a two-stage deep learning approach on standard T2-weighted MRI
inferred← citeshttps://doi.org/10.1007/s00330-024-11312-3openalex-snapshot
Multi-site, multi-vendor development and validation of a deep learning model for liver stiffness prediction using abdominal biparametric MRI
inferred← citeshttps://doi.org/10.1007/s00330-026-12448-0openalex-snapshot
Development and validation of a deep learning model for liver shear stiffness regression using abdominal multiparametric MRI across multiple sites and vendors
inferred← citeshttps://doi.org/10.1007/s11548-026-03790-1openalex-snapshot
A U-Net Transformer for magnetic resonance elastography
inferred← citeshttps://doi.org/10.1016/j.mri.2026.110801openalex-snapshot
Research progress of virtual magnetic resonance elastography
inferred← citeshttps://doi.org/10.1109/icaiss61471.2025.11041809openalex-snapshot
A Systematic Review of Deep Learning Algorithms for Non-Alcoholic Fatty Liver Disease
inferred← citeshttps://doi.org/10.1109/iciet70550.2026.11712871openalex-snapshot
Hybrid Deep Feature Extraction with PCA-Optimized Machine Learning Models for Fatty Liver Classification in Ultrasound Images
inferred← citeshttps://doi.org/10.1109/incet64471.2025.11140015openalex-snapshot
Hybrid Neural Network Framework for Multiclass Classification of Kidney Stones from CT scans
inferred← citeshttps://doi.org/10.1109/mmul.2025.3607436openalex-snapshot
A Multi-Modal Deep Fusion Network: Enhancing Graft Survival Prediction in Non-Alcoholic Fatty Liver Disease Patients Prior to Liver Transplantation
inferred← citeshttps://doi.org/10.1148/rg.240048openalex-snapshot
MASLD: What We Have Learned and Where We Need to Go—A Call to Action
inferred← citeshttps://doi.org/10.1148/ryai.210026openalex-snapshot
Classification of Multiple Diseases on Body CT Scans Using Weakly Supervised Deep Learning
inferred← citeshttps://doi.org/10.1186/s12880-025-01701-5openalex-snapshot
Deep learning approaches for classification tasks in medical X-ray, MRI, and ultrasound images: a scoping review
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3353868/v1openalex-snapshot
Radiomics unleashed: the power of DCE+DWI MRI models in predicting breast cancer recurrence and metastasis
inferred← citeshttps://doi.org/10.3348/kjr.2025.0966openalex-snapshot
Imaging Evaluation for Steatotic Liver Disease
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