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Congress: ECR25
Poster Number: C-15813
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-15813
Authorblock: Y. Kim, S. M. Ko, G. An, G. S. Kim, S. Cha; Wonju-si/KR
Disclosures:
Yeonjun Kim: Author: First Author
Sung Min Ko: Author: Corresponding Author
Giyong An: Author: Second Author
Gyeong Seop Kim: Author: Second Author
Sungjin Cha: Author: Second Author
Keywords: Cardiac, Cardiovascular system, Emergency, CT, CT-Angiography, Image manipulation / Reconstruction, Comparative studies, Technical aspects, Technology assessment, Image verification
Purpose

Purpose: Advancements in artificial intelligence (AI) have brought significant changes to medical imaging, introducing new approaches to image reconstruction. In coronary computed tomography angiography (CCTA), traditional iterative reconstruction methods have long been used as the standard for noise reduction, but they have certain limitations in balancing image clarity and accuracy. This study evaluates whether the newly developed AI-based reconstruction algorithm, DELTA, can improve image quality while maintaining diagnostic reliability compared to conventional techniques. By analyzing both objective metrics and qualitative assessments from radiologists, we aim to assess the potential impact of AI-driven reconstruction on cardiac CT imaging.

GALLERY