Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging
Purpose To describe and evaluate a new fully automated musculoskeletal tissue
segmentation method using deep convolutional neural network (CNN) and three …
segmentation method using deep convolutional neural network (CNN) and three …
Deep convolutional neural network for segmentation of knee joint anatomy
Purpose To describe and evaluate a new segmentation method using deep convolutional
neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex …
neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex …
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 …
Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative
We present a method for the automated segmentation of knee bones and cartilage from
magnetic resonance imaging (MRI) that combines a priori knowledge of anatomical shape …
magnetic resonance imaging (MRI) that combines a priori knowledge of anatomical shape …
SUSAN: segment unannotated image structure using adversarial network
F Liu - Magnetic resonance in medicine, 2019 - Wiley Online Library
Purpose To describe and evaluate a segmentation method using joint adversarial and
segmentation convolutional neural network to achieve accurate segmentation using …
segmentation convolutional neural network to achieve accurate segmentation using …
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 …
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 …
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 …
Fully automatic knee bone detection and segmentation on three-dimensional MRI
In the medical sector, three-dimensional (3D) images are commonly used like computed
tomography (CT) and magnetic resonance imaging (MRI). The 3D MRI is a non-invasive …
tomography (CT) and magnetic resonance imaging (MRI). The 3D MRI is a non-invasive …
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 …
segmentation from conventional techniques to deep learning (DL) based techniques. Knee …