사후전산화단층촬영의 법의병리학 분야 활용을 위한 조건부 적대적 생성 신경망을 이용한 CT 영상의 해상도 개선: 팬텀 연구

• 영문명: Enhancing CT Image Quality Using Conditional Generative Adversarial Networks for Applying Post-mortem Computed Tomography in Forensic Pathology: A Phantom Study
• 발행기관: 대한방사선과학회(구 대한방사선기술학회)
• 저자명: 윤예빈 허진행 김예지 조혜진 윤용수
• 간행물 정보: 『방사선기술과학』제46권 제4호, 315~323쪽, 전체 9쪽
• 주제분류: 의약학 > 방사선과학
• 파일형태: PDF
• 발행일자: 2023.08.31

영문 초록

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

목차

Ⅰ. 서 론

Ⅱ. 대상 및 방법

Ⅲ. 결 과

Ⅳ. 고 찰

Ⅴ. 결 론

REFERENCES

키워드

법의병리학 사후전산화단층촬영 심층학습 조건부 적대적 생성 신경망 해상도 Forensic pathology Post-mortem computed tomography Deep learning Conditional generative adversarial networks Resolution