A review on segmentation of knee articular cartilage: from conventional methods towards deep learning

S Ebrahimkhani, MH Jaward, FM Cicuttini… - Artificial intelligence in …, 2020 - Elsevier
In this paper, we review the state-of-the-art approaches for knee articular cartilage
segmentation from conventional techniques to deep learning (DL) based techniques. Knee …

From classical to deep learning: review on cartilage and bone segmentation techniques in knee osteoarthritis research

HS Gan, MH Ramlee, AA Wahab, YS Lee… - Artificial Intelligence …, 2021 - Springer
Knee osteoarthritis is a major diarthrodial joint disorder with profound global socioeconomic
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …

Segmentation of joint and musculoskeletal tissue in the study of arthritis

V Pedoia, S Majumdar, TM Link - Magnetic Resonance Materials in …, 2016 - Springer
As the most frequent cause of physical disability, musculoskeletal diseases such as arthritis
and osteoporosis have a great social and economical impact. Quantitative magnetic …

Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative

EB Dam, M Lillholm, J Marques… - Journal of Medical …, 2015 - spiedigitallibrary.org
Clinical studies including thousands of magnetic resonance imaging (MRI) scans offer
potential for pathogenesis research in osteoarthritis. However, comprehensive quantification …

Automatic knee cartilage segmentation from multi-contrast MR images using support vector machine classification with spatial dependencies

K Zhang, W Lu, P Marziliano - Magnetic resonance imaging, 2013 - Elsevier
Accurate segmentation of knee cartilage is required to obtain quantitative cartilage
measurements, which is crucial for the assessment of knee pathology caused by …

Fully automated segmentation of cartilage from the MR images of knee using a multi‐atlas and local structural analysis method

JG Lee, S Gumus, CH Moon, CK Kwoh… - Medical …, 2014 - Wiley Online Library
Purpose: To develop a fully automated method to segment cartilage from the magnetic
resonance (MR) images of knee and to evaluate the performance of the method on a public …

Learning-based cost functions for 3-D and 4-D multi-surface multi-object segmentation of knee MRI: data from the osteoarthritis initiative

S Kashyap, H Zhang, K Rao… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
A fully automated knee magnetic resonance imaging (MRI) segmentation method to study
osteoarthritis (OA) was developed using a novel hierarchical set of random forests (RF) …

Transformer-based multilevel region and edge aggregation network for magnetic resonance image segmentation

S Chen, L Zhong, C Qiu, Z Zhang, X Zhang - Computers in Biology and …, 2023 - Elsevier
To improve the quality of magnetic resonance (MR) image edge segmentation, some
researchers applied additional edge labels to train the network to extract edge information …

Automatic hip cartilage segmentation from 3D MR images using arc-weighted graph searching

Y **a, SS Chandra, C Engstrom… - Physics in Medicine …, 2014 - iopscience.iop.org
Accurate segmentation of hip joint cartilage from magnetic resonance (MR) images offers
opportunities for quantitative investigations of pathoanatomical conditions such as …

Personalized knee geometry modeling based on multi-atlas segmentation and mesh refinement

FP Nikolopoulos, EI Zacharaki, D Stanev… - IEEE …, 2020 - ieeexplore.ieee.org
The development of personalized finite element models of the knee anatomy is critically
important in the simulation of knee joint mechanics, prediction of optimal treatments in cases …