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Quantitative Measurement Method for Possible Rib Fractures in Chest Radiographs

Authors
 Jaeil Kim  ;  Sungjun Kim  ;  Young Jae Kim  ;  Kwang Gi Kim  ;  Jinah Park 
Citation
 HEALTHCARE INFORMATICS RESEARCH, Vol.19(3) : 196-204, 2013 
Journal Title
 HEALTHCARE INFORMATICS RESEARCH 
ISSN
 2093-3681 
Issue Date
2013
Keywords
Computer-Aided Radiographic Image Interpretation ; Decision Support Techniques ; Image Processing ; Radiography ; Rib Fractures
Abstract
OBJECTIVES: This paper proposes a measurement method to quantify the abnormal characteristics of the broken parts of ribs using local texture and shape features in chest radiographs. METHODS: OUR MEASUREMENT METHOD COMPRISES TWO STEPS: a measurement area assignment and sampling step using a spline curve and sampling lines orthogonal to the spline curve, and a fracture-ness measurement step with three measures, asymmetry and gray-level co-occurrence matrix based measures (contrast and homogeneity). They were designed to quantify the regional shape and texture features of ribs along the centerline. The discriminating ability of our method was evaluated through region of interest (ROI) analysis and rib fracture classification test using support vector machine. RESULTS: The statistically significant difference was found between the measured values from fracture and normal ROIs; asymmetry (p < 0.0001), contrast (p < 0.001), and homogeneity (p = 0.022). The rib fracture classifier, trained with the measured values in ROI analysis, detected every rib fracture from chest radiographs used for ROI analysis, but it also classified some unbroken parts of ribs as abnormal parts (8 to 17 line sets; length of each line set, 2.998 ± 2.652 mm; length of centerlines, 131.067 ± 29.460 mm). CONCLUSIONS: Our measurement method, which includes a flexible measurement technique for the curved shape of ribs and the proposed shape and texture measures, could discriminate the suspicious regions of ribs for possible rib fractures in chest radiographs.
Files in This Item:
T201303987.pdf Download
DOI
10.4258/hir.2013.19.3.196
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungjun(김성준) ORCID logo https://orcid.org/0000-0002-7876-7901
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/88424
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