Medical image processing and analysis of MRI images for Sarcopenia detection
Sarcopenia is characterized as the degenerative loss of muscle mass and function and it is associated with several major age-related clinical conditions. The reduction in muscle size could be characterized by the replacement of muscle fibers with fats and is systematically occurring throughout the s...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/68428 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-68428 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-684282023-03-03T15:41:33Z Medical image processing and analysis of MRI images for Sarcopenia detection Goh, Ying Hong Poh Chueh Loo School of Chemical and Biomedical Engineering DRNTU::Science::Medicine::Biomedical engineering Sarcopenia is characterized as the degenerative loss of muscle mass and function and it is associated with several major age-related clinical conditions. The reduction in muscle size could be characterized by the replacement of muscle fibers with fats and is systematically occurring throughout the skeletal muscles with different extent and velocity affecting the muscle function and mobility performance. The project aims to study the pattern of fat infiltrations and identify the correlation of the skeletal muscle and fat composition with CSHA clinical frailty scale through a quantitative analysis based on the MRI images. The study focus on the muscle group along the patella which were more susceptible to age related atrophy. The statistical difference were observed in the intramuscular fat volume and fat density between the CSHA groups and normal young patient between the ages of 20 – 30 years old. These differences suggested that composition of intramuscular fats and fat density in the body could potentially help identify the level of frailty and sarcopenia of the patient. The texture of the muscle were also significantly different between the CSHA groups and normal young patient between the ages of 20 – 30 years old. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2016-05-26T02:08:36Z 2016-05-26T02:08:36Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68428 en Nanyang Technological University 40 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Science::Medicine::Biomedical engineering |
spellingShingle |
DRNTU::Science::Medicine::Biomedical engineering Goh, Ying Hong Medical image processing and analysis of MRI images for Sarcopenia detection |
description |
Sarcopenia is characterized as the degenerative loss of muscle mass and function and it is associated with several major age-related clinical conditions. The reduction in muscle size could be characterized by the replacement of muscle fibers with fats and is systematically occurring throughout the skeletal muscles with different extent and velocity affecting the muscle function and mobility performance. The project aims to study the pattern of fat infiltrations and identify the correlation of the skeletal muscle and fat composition with CSHA clinical frailty scale through a quantitative analysis based on the MRI images. The study focus on the muscle group along the patella which were more susceptible to age related atrophy. The statistical difference were observed in the intramuscular fat volume and fat density between the CSHA groups and normal young patient between the ages of 20 – 30 years old. These differences suggested that composition of intramuscular fats and fat density in the body could potentially help identify the level of frailty and sarcopenia of the patient. The texture of the muscle were also significantly different between the CSHA groups and normal young patient between the ages of 20 – 30 years old. |
author2 |
Poh Chueh Loo |
author_facet |
Poh Chueh Loo Goh, Ying Hong |
format |
Final Year Project |
author |
Goh, Ying Hong |
author_sort |
Goh, Ying Hong |
title |
Medical image processing and analysis of MRI images for Sarcopenia detection |
title_short |
Medical image processing and analysis of MRI images for Sarcopenia detection |
title_full |
Medical image processing and analysis of MRI images for Sarcopenia detection |
title_fullStr |
Medical image processing and analysis of MRI images for Sarcopenia detection |
title_full_unstemmed |
Medical image processing and analysis of MRI images for Sarcopenia detection |
title_sort |
medical image processing and analysis of mri images for sarcopenia detection |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68428 |
_version_ |
1759858412876726272 |