An Automatic Detection Method for Carotid Artery Calcifications Using Top-Hat Filter on Dental Panoramic Radiographs

Tsuyoshi SAWAGASHIRA  Tatsuro HAYASHI  Takeshi HARA  Akitoshi KATSUMATA  Chisako MURAMATSU  Xiangrong ZHOU  Yukihiro IIDA  Kiyoji KATAGI  Hiroshi FUJITA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.8   pp.1878-1881
Publication Date: 2013/08/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.1878
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
Keyword: 
carotid artery,  calcification,  top-hat transform,  dental panoramic radiograph,  computer-aided detection,  

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Summary: 
The purpose of this study is to develop an automated scheme of carotid artery calcification (CAC) detection on dental panoramic radiographs (DPRs). The CAC is one of the indices for predicting the risk of arteriosclerosis. First, regions of interest (ROIs) that include carotid arteries are determined on the basis of inflection points of the mandibular contour. Initial CAC candidates are detected by using a grayscale top-hat filter and a simple grayscale thresholding technique. Finally, a rule-based approach and a support vector machine to reduce the number of false positive (FP) findings are applied using features such as area, location, and circularity. A hundred DPRs were used to evaluate the proposed scheme. The sensitivity for the detection of CACs was 90% with 4.3 FPs (80% with 1.9 FPs) per image. Experiments show that our computer-aided detection scheme may be useful to detect CACs.