[HTML][HTML] Automated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning
Background This study aimed to build a deep learning model to automatically segment
heterogeneous clinical MRI scans by optimizing a pre-trained model built from a …
heterogeneous clinical MRI scans by optimizing a pre-trained model built from a …
Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks
Purpose Fully automatic tissue segmentation is an essential step to translate quantitative
MRI techniques to clinical setting. The goal of this study was to develop a novel approach …
MRI techniques to clinical setting. The goal of this study was to develop a novel approach …
The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset
Purpose To organize a multi-institute knee MRI segmentation challenge for characterizing
the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring …
the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring …
Generalizability of deep learning segmentation algorithms for automated assessment of cartilage morphology and MRI relaxometry
AM Schmidt, AD Desai, LE Watkins… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Deep learning (DL)‐based automatic segmentation models can expedite
manual segmentation yet require resource‐intensive fine‐tuning before deployment on new …
manual segmentation yet require resource‐intensive fine‐tuning before deployment on new …
Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative
Objectives Accurate and efficient knee cartilage and bone segmentation are necessary for
basic science, clinical trial, and clinical applications. This work tested a multi-stage …
basic science, clinical trial, and clinical applications. This work tested a multi-stage …
BCD-NET: a novel method for cartilage segmentation of knee MRI via deep segmentation networks with bone-cartilage-complex modeling
Segmentation of cartilage in knee MRI is an important process for various clinical tasks in
diagnosis and treatment planning of osteoarthritis. Recently, the deep segmentation …
diagnosis and treatment planning of osteoarthritis. Recently, the deep segmentation …
Comparative study of encoder-decoder-based convolutional neural networks in cartilage delineation from knee magnetic resonance images
CW Yong, KW Lai, BP Murphy… - Current Medical Imaging …, 2021 - benthamdirect.com
Background: Osteoarthritis (OA) is a common degenerative joint inflammation that may lead
to disability. Although OA is not lethal, this disease will remarkably affect patient's mobility …
to disability. Although OA is not lethal, this disease will remarkably affect patient's mobility …
Automated segmentation of knee articular cartilage: Joint deep and hand-crafted learning-based framework using diffeomorphic mapping
Segmentation of knee articular cartilage tissue (ACT) from 3D magnetic resonance images
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
Collaborative multi-agent learning for MR knee articular cartilage segmentation
The 3D morphology and quantitative assessment of knee articular cartilages (ie, femoral,
tibial, and patellar cartilage) in magnetic resonance (MR) imaging is of great importance for …
tibial, and patellar cartilage) in magnetic resonance (MR) imaging is of great importance for …
Deep learning‐based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative
Morphological changes in knee cartilage subregions are valuable imaging‐based
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
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