NDLI: Magnetic resonance image segmentation for knee osteoarthritis using active shape models

Content Provider	IEEE Xplore Digital Library
Author	Sarah Samson Soh Swee, Tan Tian Sim Siew Ying Chuah Zhi En bin Mazenan, Mohd Nizam Leong Kah Meng
Copyright Year	2014
Description	Author affiliation: IJN-UTM Cardiovascular Engineering Centre, Medical Implant Technology Group (MediTEG), Material Manufacturing Research Alliance (MMRA), Department of Biotechnology & Medical Engineering, Faculty of Biosciences and Medical Engineering (FBME), Universiti Teknologi Malaysia (UTM), 81310 Skudai Johor, Malaysia (Sarah Samson Soh; Swee, Tan Tian; Sim Siew Ying; Chuah Zhi En; bin Mazenan, Mohd Nizam; Leong Kah Meng)
Abstract	Knee osteoarthritis is a chronic joint inflammation disease that affects the aged population nowadays. The disease leads to gradual degradation of cartilage and thus deteriorates the function of the knee joint. Magnetic Resonance Imaging (MRI) provides promising results for the early detection of knee osteoarthritis. Conventionally, the MR image segmentation for knee osteoarthritis is manually done by clinicians. Limitations of this process include being laborious, time-consuming and prone to subjective diagnosis error. Therefore, the development of an automated cartilage segmentation method is crucial to assist the medical research in knee osteoarthritis. This project applied the Active Shape Models (ASM) approach to create semi-automated cartilage segmentation software. A shape model was constructed from a training set consisting of 10 knee MR images which includes major variations of the knee cartilage shape. Principle component analysis (PCA) was utilized to identify the main axes of variations used to build the shape model. This shape model was finally used to segment the knee articular cartilage. Outcomes of the ASM segmentation were compared with the outcome of manual segmentation. Experimental results showed that the sensitivity of developed ASM approach increased averagely from 73.78% to 80.75%, proportional to the increasing of the number of iteration in the segmentation as well as landmark of the shape model. This technique is reliable to contribute to medical research in knee osteoarthritis by providing an efficient and high accuracy segmentation method for knee articular cartilage, to further assist in the detection of knee osteoarthritis via MRI technique.
Starting Page	1
Ending Page	5
File Size	1069272
Page Count	5
File Format	PDF
ISBN	9781479968015
DOI	10.1109/BMEiCON.2014.7017365
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-26
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Analytical models Active Shape Models Biological system modeling Magnetic resonance imaging Segmentation MRI Knee Articular Cartilage Materials Lead Principal Component Analysis Biomedical imaging
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Segmentation of articular cartilage using active contours and prior knowledge

Active appearance models for segmentation of cardiac MRI data

3-D knee cartilage segmentation using a smoothing B-Spline active surface

Automatic segmentation of bones and inter-image anatomical correspondence by volumetric statistical modelling of knee MRI

Automatic Human Knee Cartilage Segmentation From 3-D Magnetic Resonance Images

Knee joint cartilage visualization and quantification in normal and osteoarthritis

Regional quantitative analysis of knee cartilage in a population study using MRI and model based correspondences

Semi-automatic segmentation of knee osteoarthritic cartilage in magnetic resonance images

Combined Image Processing Techniques for Characterization of MRI Cartilage of the Knee

Magnetic resonance image segmentation for knee osteoarthritis using active shape models

Similar Documents

Segmentation of articular cartilage using active contours and prior knowledge

Active appearance models for segmentation of cardiac MRI data

3-D knee cartilage segmentation using a smoothing B-Spline active surface

Automatic segmentation of bones and inter-image anatomical correspondence by volumetric statistical modelling of knee MRI

Automatic Human Knee Cartilage Segmentation From 3-D Magnetic Resonance Images

Knee joint cartilage visualization and quantification in normal and osteoarthritis

Regional quantitative analysis of knee cartilage in a population study using MRI and model based correspondences

Semi-automatic segmentation of knee osteoarthritic cartilage in magnetic resonance images

Combined Image Processing Techniques for Characterization of MRI Cartilage of the Knee

Magnetic resonance image segmentation for knee osteoarthritis using active shape models