Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/68456
Title: Medical image processing and analysis of MRI images for Sacropenia detection
Authors: Bose, Michael Raj
Keywords: DRNTU::Science::Medicine::Biomedical engineering
Issue Date: 2016
Abstract: The main focus of this report is on Sacropenia. It is a syndrome characterized by the progressive loss of muscle mass as an individual age. Studies have shown that Sacropenia is a key factor to the pathophysiology of frailty due to the loss of muscle mass. However, using this as an indicator alone has proven to be not as conclusive. The quantification of fat infiltrates into the different muscle groups has become integral through the various studies that have identified the relationship between buildup of fat infiltrates and frailty. To be able to understand how this relationship works, a more comprehensive study has to be conducted. Segmenting the fat infiltrates from the muscle groups in the MRI images is integral to the analysis of Sacropenia. However, the current semi-automatic methods are limited in accuracy and thus, manual segmentation is approached. Manual segmentation is unfortunately; very tedious and time-consuming even to a trained professional. An improvement to the current semi-automatic methods would be beneficial. This project aims to serve as a base to improving the current methods of segmentation. A better understanding of how the fat infiltrates and muscle are distributed will be identified. Identifying a possible trend between the how the fat infiltrates and muscle are distributed, will greatly simplify the algorithm applied in the programme to identify Sacropenia and frailty. Sacropenia can cause loss of muscle mass, degradation and loss of function. By eventually inventing a method to detect the condition early, the effects of Sacropenia can be lessened.
URI: http://hdl.handle.net/10356/68456
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Student Reports (FYP/IA/PA/PI)

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