| Izvleček: | This project looks specifically into Sarcopenia, a syndrome characterized by the
progressive loss of muscle mass associated with age. Sarcopenia is the central factor
in the pathophysiology of frailty.
The quantification of muscular fat infiltrates has become increasingly important, as a
number of researches have identified a relationship between the accumulation of fat
infiltrates and frailty. Therefore, the ability to quantify fats efficiently and accurately
is significant for further analysis of this field.
Segmenting the fat infiltrates from medical images is a crucial step towards their
quantification and visualization. However, there is no previous work performed on
semi-automatic or fully automatic segmentation of fat infiltrates. Mostly still depend
heavily on manual segmentation that is both tedious and time-consuming. Hence, the
aim of this project is to develop an automated segmentation program for the
extraction of fat infiltrates from MRI images of the knee muscle.
In this project, several procedures for a snake active contour program automated
successfully. Most importantly, the choosing of initialization points and the
processing of all slices associated with a particular muscle group. In addition, several
problems with the accuracy of segmentation were also identified, with the
background intensity being the most crucial factor. Deeper analysis was carried out
to obtain the optimal factor for segmentation.
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