[논문 정리] CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline

논문정보CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline - ScienceDirect GitHub - ales-git/DeepCADRADS: CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: a clinically-ins..

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• · 2025. 6. 4.
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[논문 정리] Improved Cascade-RCNN for automatic detection of coronary artery plaque in multi-angle fusion CPR images

논문정보 Improved Cascade-RCNN for automatic detection of coronary artery plaque in multi-angle fusion CPR images 논문정리Abstract관상동맥 심장병은 관상동맥의 artherosclerosis(죽상경화), spasm(경련)으로 인해 플라크가 형성되면서 발생관상동맥 플라크를 의료 영상으로 탐지하면 비파괴적이고 빠르게 진단, 의학적/임상적 가치 highCTA 영상 시퀀스를 기반으로 한 관상동맥의 위험 플라크를 자동으로 탐지하는 방법 제안총 132명 환자에게서 CAT 영상 시퀀스 수집, 3D segmentation을 통해 관상동맥 트리 구조 추출관상동맥의 centerline은 skeleton thinning 기법을 통해 추출단..

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• · 2025. 6. 2.
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[논문 정리] Coronary R-CNN: Vessel-Wise Method for Coronary Artery Lesion Detection and Analysis in Coronary CT Angiography

논문정보Coronary R-CNN: Vessel-Wise Method for Coronary Artery Lesion Detection and Analysis in Coronary CT Angiography Coronary R-CNN: Vessel-wise Method for Coronary Artery Lesion Detection and Analysis in Coronary CT AngiographyPaper Info Reviews Meta-review Author Feedback Post-Rebuttal Meta-reviews Authors Yu Zhang, Jun Ma, Jing Li Abstract In recent decades, coronary artery disease (CAD) is th..

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• · 2025. 5. 30.
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[논문 정리] Deep Learning-Based Automated Quantification of Coronary Artery Calcification for Contrast-Enhanced Coronary Computed Tomographic Angiography

논문정보Deep Learning-Based Automated Quantification of Coronary Artery Calcification for Contrast-Enhanced Coronary Computed Tomographic Angiography논문정리Abstract향상된 ECG-gated CCTA(coronary CT angiography)를 기반으로 한 딥러닝 기반 자동 정량화 알고리즘의 관상동맥 석회화 (CAC, coronary artery calcium) 측정 정확도를 CT(CSCT)로 평가함즉, 딥러닝이 석회화를 얼마나 정확하게 잘 뽑는지를 확인CSCT조영제 없이 촬영해서 관상동맥에 칼슘(석회화)이 얼마나 쌓였는지 점수화하는 CT심혈관 질환 위험 예측에 사용됨* 왜 CSCT는 조영..

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• · 2025. 5. 4.
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[논문 정리] A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software

논문정보A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software논문정리1. AbstractCCTA(coronary computed tomography angiography) 이미지를 이용해서 관상동맥(coronary artery)를 자동으로 세그멘테이션하면, CAD(coronary artery diesease) 관련 분석을 더 쉽게 할 수 있다. 루멘(lumen)이나 플라크(plaque) 부위를 정확하게 중요하는 것이 중요함! CCTA 관상동맥 CT 혈관조영술심장의 관상동맥을 비침습적으로 촬영하여, 혈관이 좁아졌는지(협착..

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• · 2025. 4. 30.
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[논문 정리] Delving into Multimodal Prompting for Fine-grained Visual Classification

논문정보Delving into Multimodal Prompting for Fine-grained Visual Classification Delving into Multimodal Prompting for Fine-grained Visual ClassificationFine-grained visual classification (FGVC) involves categorizing fine subdivisions within a broader category, which poses challenges due to subtle inter-class discrepancies and large intra-class variations. However, prevailing approaches primarily fo..

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• · 2024. 8. 22.
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