CartiMorph: A framework for automated knee articular cartilage morphometrics

Y Yao, J Zhong, L Zhang, S Khan, W Chen - Medical Image Analysis, 2024 - Elsevier
We introduce CartiMorph, a framework for automated knee articular cartilage
morphometrics. It takes an image as input and generates quantitative metrics for cartilage …

Automated measurement and grading of knee cartilage thickness: a deep learning-based approach

JR Guo, P Yan, Y Qin, MN Liu, Y Ma, JQ Li… - Frontiers in …, 2024 - frontiersin.org
Background Knee cartilage is the most crucial structure in the knee, and the reduction of
cartilage thickness is a significant factor in the occurrence and development of osteoarthritis …

NEURALSEG: state-of-the-art cartilage segmentation using deep learning–analyses of data from the osteoarthritis initiative

AA Gatti - Osteoarthritis and Cartilage, 2018 - oarsijournal.com
Purpose: Morphologic assessment of cartilage obtained using magnetic resonance imaging
(MRI) is of particular interest for osteoarthritis (OA) research. A primary limitation of MRI for …

Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative

AA Gatti, MR Maly - Magnetic Resonance Materials in Physics, Biology …, 2021 - Springer
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 …

A framework for optimizing measurement weight maps to minimize the required sample size

AA Qazi, DR Jørgensen, M Lillholm, M Loog… - Medical Image …, 2010 - Elsevier
We propose a fully automatic statistical framework for identifying the non-negative, real-
valued weight map that best discriminate between two groups of objects. Given …

[HTML][HTML] Agreement and accuracy of fully automated morphometric femorotibial cartilage analysis in radiographic knee osteoarthritis

F Eckstein, AS Chaudhari, J Kemnitz… - Osteoarthritis …, 2023 - Elsevier
Objective To examine the performance of automated convolutional neuronal network
cartilage segmentation in knees with radiographic osteoarthritis (ROA), and its dependence …

Accurate automated volumetry of cartilage of the knee using convolutional neural networks: data from the osteoarthritis initiative

A Tack, S Zachow - 2019 IEEE 16th International Symposium …, 2019 - ieeexplore.ieee.org
Volumetry of the cartilage of the knee, as needed for the assessment of knee osteoarthritis
(KOA), is typically performed in a tedious and subjective process. We present an automated …

[HTML][HTML] Deep learning for chondrocyte identification in automated histological analysis of articular cartilage

L Yang, MC Coleman, MR Hines, PN Kluz… - The Iowa orthopaedic …, 2019 - ncbi.nlm.nih.gov
Background: Histology-based methods are commonly used in osteoarthritis (OA) research
because they provide detailed information about cartilage health at the cellular and tissue …

Deep learning‐based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative

E Panfilov, A Tiulpin, MT Nieminen… - Journal of …, 2022 - Wiley Online Library
Morphological changes in knee cartilage subregions are valuable imaging‐based
biomarkers for understanding progression of osteoarthritis, and they are typically detected …

[HTML][HTML] Equivalence and precision of knee cartilage morphometry between different segmentation teams, cartilage regions, and MR acquisitions

E Schneider, M Nevitt, C McCulloch, FM Cicuttini… - Osteoarthritis and …, 2012 - Elsevier
OBJECTIVE: To compare precision and evaluate equivalence of femorotibial cartilage
volume (VC) and mean cartilage thickness over total area of bone (ThCtAB. Me) from …