Paper Info
Title
Computer Vision Based Automatic Extraction and Thickness Measurement of Deep Cervical Flexor from Ultrasonic Images.
Abstract
Deep Cervical Flexor (DCF) muscles are important in monitoring and controlling neck pain. While ultrasonographic analysis is useful in this area, it has intrinsic subjectivity problem. In this paper, we propose automatic DCF extractor/analyzer software based on computer vision. One of the major difficulties in developing such an automatic analyzer is to detect important organs and their boundaries under very low brightness contrast environment. Our fuzzy sigma binarization process is one of the answers for that problem. Another difficulty is to compensate information loss that happened during such image processing procedures. Many morphologically motivated image processing algorithms are applied for that purpose. The proposed method is verified as successful in extracting DCFs and measuring thicknesses in experiment using two hundred 800 x 600 DICOM ultrasonography images with 98.5% extraction rate. Also, the thickness of DCFs automatically measured by this software has small difference (less than 0.3 cm) for 89.8% of extracted DCFs.
Year
DOI
Venue
2016
10.1155/2016/5892051
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Field
DocType
Volume
Computer vision,Ultrasonic sensor,DICOM,Computer science,Fuzzy logic,Image processing,Automation,Software,Artificial intelligence,Digital image processing,Spectrum analyzer
Journal
2016
ISSN
Citations 
PageRank 
1748-670X
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
kwangbaek kim111043.94
Doo Heon Song2176.52
Hyun Jun Park323.08