흉부 방사선영상의 좌, 우 반전 발생 여부 컨벌루션 신경망 기반 정확도 평가

• 영문명: An Accuracy Evaluation on Convolutional Neural Network Assessment of Orientation Reversal of Chest X-ray Image
• 발행기관: 대한방사선과학회(구 대한방사선기술학회)
• 저자명: 이현우(Hyun-Woo Lee) 오주영(Joo-Young Oh) 이주영(Joo-Young Lee) 이태수(Tae-Soo Lee) 박훈희(Hoon-Hee Park)
• 간행물 정보: 『방사선기술과학』방사선기술과학 제43권 제2호, 65~70쪽, 전체 6쪽
• 주제분류: 의약학 > 방사선과학
• 파일형태: PDF
• 발행일자: 2020.04.30

영문 초록

PA(postero-anterior) and AP(antero-posterior) chest projections are the most sought-after types of all kinds of projections. But if a radiological technologist puts wrong information about the position in the computer, the orientation of left and right side of an image would be reversed. In order to solve this problem, we utilized CNN(convolutional neural network) which has recently utilized a lot for studies of medical imaging technology and rule-based system. 70% of 111,622 chest images were used for training, 20% of them were used for testing and 10% of them were used for validation set in the CNN experiment. The same amount of images which were used for testing in the CNN experiment were used in rule-based system. Python 3.7 version and Tensorflow r1.14 were utilized for data environment. As a result, rule-based system had 66% accuracy on evaluating whether the orientation reversal on chest x-ray image. But the CNN had 97.9% accuracy on that. Being overcome limitations by CNN which had been shown on rule-based system and shown the high accuracy can be considered as a meaningful result. If some problems which can occur for tasks of the radiological technologist can be separated by utilizing CNN, It can contribute a lot to optimize workflow.

목차

Ⅰ. 서 론

Ⅱ. 대상 및 방법

Ⅲ. 결 과

Ⅳ. 고 찰

Ⅴ. 결 론

키워드

흉부검사(Chest projection) 방사선영상(X-ray image) 방향반전(Orientation reversal) 규칙기반 시스템(Rule-based system) 컨벌루션 신경망(Convolutional neural network)