Development and Validation of AI System for AAS CTA Diagnosis and Mapping
收藏DataCite Commons2026-04-10 更新2026-05-04 收录
下载链接：
https://data.mendeley.com/datasets/cwzxbpdh7h/2
下载链接
链接失效反馈官方服务：
资源简介：
AAS-DSS: AI-Powered Acute Aortic Syndrome Decision Support System Code
This repository contains the code for AAS-DSS, a Python-based pipeline for automated detection/classification of acute aortic syndrome (AAS) subtypes (AD, IMH, PAU) using CTA images.
Core Functions:
- Preprocessing & aorta mask generation via TotalSegmentator.
- Multi-class segmentation (AD/IMH/PAU) with nnUNet (requires pre-trained weights).
- Slice-level classification using custom .pth models.
- User-friendly GUI for path configuration and pipeline execution.
Prerequisites: Python 3.x, medical imaging libraries, TotalSegmentator, pre-trained model weights (per specified directories).
Input/Output: Accepts .nii.gz CTA images; outputs results to a user-specified folder. Flexible path adjustment supported.
AAS-DSS enables automated 17-zone aortic segmentation (extended SVS/STS classification) to support standardized AAS diagnosis.
提供机构：
Mendeley Data
创建时间：
2026-04-10
