Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network
Segmentation of anatomical structures in medical images is often based on a voxel/pixel
classification approach. Deep learning systems, such as convolutional neural networks …
classification approach. Deep learning systems, such as convolutional neural networks …
Automatic knee cartilage segmentation using fully volumetric convolutional neural networks for evaluation of osteoarthritis
Automated Cartilage segmentation is essential for improving the performance of advanced
Knee Osteoarthritis (OA) assessment due to its convoluted 3D structure. In this paper, we …
Knee Osteoarthritis (OA) assessment due to its convoluted 3D structure. In this paper, we …
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 …
[PDF][PDF] Segmentation of knee images: a grand challenge
In this paper, we present an evaluation framework for the 3D segmentation of knee bones
and cartilage from magnetic resonance images. The framework was established for one of …
and cartilage from magnetic resonance images. The framework was established for one of …
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 …
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 …
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 …
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 …
Segmenting articular cartilage automatically using a voxel classification approach
J Folkesson, EB Dam, OF Olsen… - IEEE transactions on …, 2006 - ieeexplore.ieee.org
We present a fully automatic method for articular cartilage segmentation from magnetic
resonance imaging (MRI) which we use as the foundation of a quantitative cartilage …
resonance imaging (MRI) which we use as the foundation of a quantitative cartilage …
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 …