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 …
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 …
Use of 2D U-Net convolutional neural networks for automated cartilage and meniscus segmentation of knee MR imaging data to determine relaxometry and …
B Norman, V Pedoia, S Majumdar - Radiology, 2018 - pubs.rsna.org
Purpose To analyze how automatic segmentation translates in accuracy and precision to
morphology and relaxometry compared with manual segmentation and increases the speed …
morphology and relaxometry compared with manual segmentation and increases the speed …
Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and
soft tissue is important to many areas of musculoskeletal research. However, methodologies …
soft tissue is important to many areas of musculoskeletal research. However, methodologies …
[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 …
Detection of differences in longitudinal cartilage thickness loss using a deep‐learning automated segmentation algorithm: Data from the Foundation for the National …
F Eckstein, AS Chaudhari, D Fuerst… - Arthritis Care & …, 2022 - Wiley Online Library
Objective To study the longitudinal performance of fully automated cartilage segmentation in
knees with radiographic osteoarthritis (OA), we evaluated the sensitivity to change in …
knees with radiographic osteoarthritis (OA), we evaluated the sensitivity to change in …
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 …
Open source software for automatic subregional assessment of knee cartilage degradation using quantitative T2 relaxometry and deep learning
Objective We evaluated a fully automated femoral cartilage segmentation model for
measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo …
measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo …
From classical to deep learning: review on cartilage and bone segmentation techniques in knee osteoarthritis research
Knee osteoarthritis is a major diarthrodial joint disorder with profound global socioeconomic
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …
Design and validation of a semi-automatic bone segmentation algorithm from MRI to improve research efficiency
LN Heckelman, BJ Soher, CE Spritzer, BD Lewis… - Scientific Reports, 2022 - nature.com
Segmentation of medical images into different tissue types is essential for many
advancements in orthopaedic research; however, manual segmentation techniques can be …
advancements in orthopaedic research; however, manual segmentation techniques can be …
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