TITLE:
Paraspinal Muscle Segmentation in CT Images Using GSM-Based Fuzzy C-Means Clustering
AUTHORS:
Yong Wei, Xiuping Tao, Bin Xu, Arend P. Castelein
KEYWORDS:
CT Image, Segmentation, Gray Space Map (GSM), Fuzzy C-Means Clustering, Minimally Invasive Spine Surgery (MISS)
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.9,
July
11,
2014
ABSTRACT:
Minimally Invasive Spine surgery (MISS) was
developed to treat disorders of the spine with less disruption to the muscles.
Surgeons use CT images to monitor the volume of muscles after operation in
order to evaluate the progress of patient recovery. The first step in the task
is to segment the muscle regions from other tissues/organs in CT images.
However, manual segmentation of muscle regions is not only inaccurate, but also
time consuming. In this work, Gray Space Map (GSM) is used in fuzzy c-means
clustering algorithm to segment muscle regions in CT images. GSM com- bines
both spatial and intensity information of pixels. Experiments show that the
proposed GSM- based fuzzy c-means clustering muscle CT image segmentation
yields very good results.