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작성자 M.I.D

[논문] Recognition for Lung Cancer using PCA in the Digital Chest Radiog…


Recognition for Lung Cancer using PCA in the Digital Chest Radiography
(디지털 흉부영상에서 주성분분서을 이용한 폐암인식)

Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)
Volume 15 Issue 7 / Pages.1573-1582 / 2011 / 2234-4772(pISSN) / 2288-4165(eISSN)
The Korea Institute of Information and Commucation Engineering (한국정보통신학회)

박형후/Park, Hyung-Hu (고신대학교대학원) ; 옥치상 / Ok, Chi-Sang (고신대학교대학원 보건과학과) ; 강세식 / Kang, Se-Sik  (부산가톨릭대학교방사선과) ; 고성진 / Ko, Sung-Jin (부산가톨릭대학교방사선과) ; 최석윤 / Choi, Seok-Yoon(부산가톨릭대학교방사선과)

Risk of lung cancer among lung-related diseases has gradually increased during last decades. The chest digital radiography is the primary diagnosis method for lung cancer. Diagnosing lung cancer using this method requires doctors of ripe experience. Despite their experience there are often wrong diagnoses, which decrease early diagnosis and survival rates of patients. The aim of this study was intended to establish the base on the Computer Aided Diagnosis (CAD) by analyzing Image Recognition Algorithm using Principle component Analysis (PCA) and diagnosing patient's chest X-ray image. The database obtained through this approach enables a doctor to significantly reduce misdiagnosis during the early diagnosis stage, if he or she utilizes it as the preliminary reading step. Case studies were carried out using normal organ, and organs suffering from bronchogenic carcinoma and granuloma. A normal image and unique disease images were extracted after PCA analysis, and their cross-recognition efficiency were compared each other. The result revealed that the recognition rate was much high between normal and disease images, but relatively low between two disease images. In order to increase the recognition efficiency among chest diseases the related algorithms have to be developed continuously in the future study, and such effort will establish the resolute base for CAD.

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