In this paper, we present a novel method for image segmentation of the hip joint structure. The key idea is to transfer the ground truth segmentation from the database to the test image. The ground truth segmentation of MR images is done by medical experts. The process includes the top down approach which register the shape of the test image globally and locally with the database of train images. The goal of top down approach is to find the best train image for each of the local test image parts. The bottom up approach replaces the local test parts by best train image parts, and inverse transform the best train image parts to represent a test image by the mosaic of best train image parts. The ground truth segmentation is transferred from be...
Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs fro...
In the process of generating image based subject specific musculoskeletal models and the simulation ...
This paper presents an automated segmentation approach for MR images of the knee bones. The bones ar...
The segmentation of medical images is a difficult task due to the inhomogeneous intensity variations...
The accurate segmentation of the bone from Magnetic Resonance (MR) images of the hip is important fo...
Automatic image analysis of magnetic resonance (MR) images of the knee is simplified by bringing the...
The accurate segmentation of the bone and articular cartilages from magnetic resonance (MR) images o...
There are several medical application areas that require the segmentation and separation of the comp...
Osteoarthritis is a degenerative joint disease which is hard to diagnose objectively and may vary ba...
Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assist...
Accurate segmentation of hip joint cartilage from magnetic resonance (MR) images provides a basis fo...
We present and validate a hybrid segmentation scheme based around 3D active shape models, which is u...
In this paper a fully automated segmentation system for the femur in the knee in Magnetic Resonance ...
By leveraging the recent development of artificial intelligence algorithms, several medical sectors ...
Osteoarthritis (OA) and Bone Marrow Edema (BME) are very common diseases of the knee. They are chara...
Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs fro...
In the process of generating image based subject specific musculoskeletal models and the simulation ...
This paper presents an automated segmentation approach for MR images of the knee bones. The bones ar...
The segmentation of medical images is a difficult task due to the inhomogeneous intensity variations...
The accurate segmentation of the bone from Magnetic Resonance (MR) images of the hip is important fo...
Automatic image analysis of magnetic resonance (MR) images of the knee is simplified by bringing the...
The accurate segmentation of the bone and articular cartilages from magnetic resonance (MR) images o...
There are several medical application areas that require the segmentation and separation of the comp...
Osteoarthritis is a degenerative joint disease which is hard to diagnose objectively and may vary ba...
Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assist...
Accurate segmentation of hip joint cartilage from magnetic resonance (MR) images provides a basis fo...
We present and validate a hybrid segmentation scheme based around 3D active shape models, which is u...
In this paper a fully automated segmentation system for the femur in the knee in Magnetic Resonance ...
By leveraging the recent development of artificial intelligence algorithms, several medical sectors ...
Osteoarthritis (OA) and Bone Marrow Edema (BME) are very common diseases of the knee. They are chara...
Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs fro...
In the process of generating image based subject specific musculoskeletal models and the simulation ...
This paper presents an automated segmentation approach for MR images of the knee bones. The bones ar...