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 …
A comprehensive survey on bone segmentation techniques in knee osteoarthritis research: From conventional methods to deep learning
Knee osteoarthritis (KOA) is a degenerative joint disease, which significantly affects middle-
aged and elderly people. The majority of KOA is primarily based on hyaline cartilage …
aged and elderly people. The majority of KOA is primarily based on hyaline cartilage …
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 …
A novel hybrid approach based on deep cnn features to detect knee osteoarthritis
In the recent era, various diseases have severely affected the lifestyle of individuals,
especially adults. Among these, bone diseases, including Knee Osteoarthritis (KOA), have a …
especially adults. Among these, bone diseases, including Knee Osteoarthritis (KOA), have a …
A survey of graph theoretical approaches to image segmentation
Image segmentation is a fundamental problem in computer vision. Despite many years of
research, general purpose image segmentation is still a very challenging task because …
research, general purpose image segmentation is still a very challenging task because …
Multiple surface segmentation using convolution neural nets: application to retinal layer segmentation in OCT images
Automated segmentation of object boundaries or surfaces is crucial for quantitative image
analysis in numerous biomedical applications. For example, retinal surfaces in optical …
analysis in numerous biomedical applications. For example, retinal surfaces in optical …
[图书][B] Guide to medical image analysis
KD Toennies - 2017 - Springer
The methodology presented in the first edition was considered established practice or
settled science in the medical image analysis community in 2010–2011. Progress in this …
settled science in the medical image analysis community in 2010–2011. Progress in this …
Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut
An automated method is reported for segmenting 3-D fluid-associated abnormalities in the
retina, so-called symptomatic exudate-associated derangements (SEAD), from 3-D OCT …
retina, so-called symptomatic exudate-associated derangements (SEAD), from 3-D OCT …
Optimal co-segmentation of tumor in PET-CT images with context information
<? Pub Dtl=""?> Positron emission tomography (PET)-computed tomography (CT) images
have been widely used in clinical practice for radiotherapy treatment planning of the …
have been widely used in clinical practice for radiotherapy treatment planning of the …
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 …