사후전산화단층촬영의 법의병리학 분야 활용을 위한 조건부 적대적 생성 신경망을 이용한 CT 영상의 해상도 개선: 팬텀 연구
Enhancing CT Image Quality Using Conditional Generative Adversarial Networks for Applying Post-mortem Computed Tomography in Forensic Pathology: A Phantom Study
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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.
Abstract
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.
참고문헌 (30)
- Chi J, "CT image super-resolution reconstruction based on global hybrid attention", Computers in Biology and Medicine, 150, pp.106112~ (2022)
- 이만구, "CT검사건수 및 CT검사에 의한 집단 실효선량의 추정", 방사선기술과학, 33(3), pp.231~238 (2010), 대한방사선과학회
- Krantz P, "Postmortem computed tomography in a diving fatality", Journal of Computer Assisted Tomography, 7(1), pp.132~134 (1983)
- Morishita J, "New solutions for automated image recognition and identification : Challenges to radiologic technology and forensic pathology", Radiological Physics and Technology, 14, pp.123~133 (2021)
- Heo JH, "The significance of evaluating sphenoid sinus fluid by postmortem computed tomography in cases of drowning", Journal of Forensic and Legal Medicine, pp.2023~102551 (2023)
- Kawazoe Y, "A simple method for semi-automatic readjustment for positioning in post-mortem head computed tomography imaging", Journal of Forensic Radiology and Imaging, 16, pp.57~64 (2019)
- Ross SG, "Postmortem CT angiography : Capabilities and limitations in traumatic and natural causes of death", Radiographics, 34(3), pp.830~846 (2014)
- Grabherr S, "Modern post-mortem imaging : An update on recent developments", Forensic Sciences Research, 2(2), pp.52~64 (2017)
- Gascho D, "Post-mortem computed tomography : Technical principles and recommended parameter settings for high-resolution imaging", Medicine, Science and the Law, 58(1), pp.70~82 (2018)
- Flach PM, "Imaging in forensic radiology : An illustrated guide for postmortem computed tomography technique and protocols", Forensic Science, Medicine, and Pathology, 10, pp.583~606 (2014)
- Kempter M, "Post-mortem imaging of laryngohyoid fractures in strangulation incidents : First results", Legal Medicine, 11(6), pp.267~271 (2009)
- Grassberger M, "3D reconstruction of emergency cranial computed tomography scans as a tool in clinical forensic radiology after survived blunt head trauma-report of two cases", Forensic Science International, 207(1-3), pp.e19~e23 (2011)[DOI]
- Sarment DP, "The use of cone beam computed tomography in forensic radiology", Journal of Forensic Radiology and Imaging, 2(4), pp.173~181 (2014)
- Thali MJ, "Virtopsy, a new imaging horizon in forensic pathology : Virtual autopsy by postmortem multislice computed tomography(MSCT)and magnetic resonance imaging(MRI)-A feasibility study", Journal of Forensic Sciences, 48(2), pp.386~403 (2003)
- 홍준용, "AI 의료영상 분석의 개요 및 연구 현황에 대한 고찰", 방사선기술과학, 43(3), pp.195~208 (2020), 대한방사선과학회
- Mirza M, "Conditional generative adversarial nets", arXiv preprint arXiv, 1411~1784 (2014)
- Zijlstra F, "CT synthesis from MR images for orthopedic applications in the lower arm using a conditional generative adversarial network", Medical Imaging 2019 : Image Processing, 10949, pp.387~393 (2019)
- Wang J, "Metal artifact reduction for the segmentation of the intra cochlear anatomy in CT images of the ear with 3D-conditional GANs", Medical Imaging Analysis, 58, pp.101553~ (2019)
- 신재훈, "안와파열골절 환자에서 중증 외상성 안구내 손상 발생과 연관인자 분석", 대한외상학회지, 22(1), pp.97~102 (2009), 대한외상학회
- 박순호, "안와골절과 동반된 안손상에 대한 임상적 고찰", 대한안과학회지, 43(8), pp.18~1481 (2002), 대한안과학회
- Kim J, "Delayed reduction of zygomatic arch fracture : Effectiveness of the Rowe Zygoma Elevator", Journal of Craniofacial Surgery, 29(7), pp.e639~e640 (2018)[DOI]
- 이주형, "측두골 외상의 진단과 치료", 대한이비인후-두경부외과학회지, 57(7), pp.433~441 (2014), 대한이비인후과학회[DOI]
- Hore A, "Image quality metrics: PSNR vs. SSIM", 2010 20th International Conference on Pattern Recognition, pp.2366~2369 (2010), IEEE
- Ding K, "Image quality assessment : Unifying structure and texture similarity", IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(5), pp.2567~2581 (2020)
- Aoki T, "Disaster victim identification using dental records-Experience of the Great East Japan Earthquake", 2013 IEEE Region 10 Humanitarian Technology Conference, pp.57~62 (2013), IEEE
- Pfaeffli M, "Post-mortem radiological CT identification based on classical ante-mortem X-ray examinations", Forensic Science International, 171(2-3), pp.111~117 (2007)
- Quatrehomme G, "Identification by frontal sinus pattern in forensic anthropology", Forensic Science International, 83(2), pp.147~153 (1996)
- Tsubaki S, "Sex determination based on a thoracic vertebra and ribs evaluation using clinical chest radiography", Legal Medicine, 27, pp.19~24 (2017)
- Kano T, "Postmortem CT morphometry with a proposal of novel parameters for sex discrimination of the mandible using Japanese adult data", Legal Medicine, 17(3), pp.167~171 (2015)
- Akhlaghi M, "Frontal sinus parameters in computed tomography and sex determination", Legal Medicine, 19, pp.22~27 (2016)