Semantic context forests for learning-based knee cartilage segmentation in 3D MR images
The automatic segmentation of human knee cartilage from 3D MR images is a useful yet
challenging task due to the thin sheet structure of the cartilage with diffuse boundaries and …
challenging task due to the thin sheet structure of the cartilage with diffuse boundaries and …
Multi-atlas context forests for knee MR image segmentation
It is important, yet a challenging procedure, to segment bones and cartilages from knee MR
images. In this paper, we propose multi-atlas context forests to first segment bones and then …
images. In this paper, we propose multi-atlas context forests to first segment bones and then …
[PDF][PDF] Learning local shape and appearance for segmentation of knee cartilage in 3D MRI
We present experimental evaluation of a new fully-automatic method for accurate knee
cartilage segmentation based on 40 test and 60 training images of the SKI10 set. The …
cartilage segmentation based on 40 test and 60 training images of the SKI10 set. The …
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 …
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 …
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 …
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 …
BCD-NET: a novel method for cartilage segmentation of knee MRI via deep segmentation networks with bone-cartilage-complex modeling
Segmentation of cartilage in knee MRI is an important process for various clinical tasks in
diagnosis and treatment planning of osteoarthritis. Recently, the deep segmentation …
diagnosis and treatment planning of osteoarthritis. Recently, the deep segmentation …
Automated segmentation of knee articular cartilage: Joint deep and hand-crafted learning-based framework using diffeomorphic mapping
Segmentation of knee articular cartilage tissue (ACT) from 3D magnetic resonance images
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
(MRIs) is a fundamental task in assessing knee osteoarthritis (KOA). However, automated …
Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images
We propose a fully automatic method for segmenting knee cartilage in 3-D MR images
which consists of bone segmentation, bone-cartilage interface (BCI) classification, and …
which consists of bone segmentation, bone-cartilage interface (BCI) classification, and …
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