胸腹部增强CT血管图像数据

采集方案：胸腹部增强CT血管图像数据包含胸部增强CT血管图像数据和腹部增强CT血管图像数据。胸部增强CT血管图像数据来自于江苏省人民医院和Pulmonary Artery Segmentation Challenge 2022挑战赛。江苏省人民医院的图像采集使用PHILIPS Brilliance256层CT机，遵循胸部CT增强扫描标准规范，由人工确认图像质量，图像以DICOM格式保存。使用SimpleITK将DICOM图像转换为去除患者隐私信息的NIfTI图像，截取肺部ROI区域并使用Frangi滤波器获得血管增强图像，进行保存。腹部增强图像来自于苏州大学附属第二医院和Kidney PArsing Challenge2022挑战赛。苏州大学附属第二医院的图像采集使用GE Healthcare LightseedVCT64排CT机，遵循腹部CT增强扫描标准规范，由人工确认图像质量，图像以DICOM格式保存。使用SimpleITK将DICOM图像转换为去除患者隐私信息的NIfTI图像，截取肾脏ROI区域进行保存。设备情况：a.PHILIPS Brilliance 256层CT机。b.GE Healthcare Lightspeed VCT64排CT机。数据集大小：9.1GB。

Data Collection Protocol: The chest and abdomen contrast-enhanced CT angiography dataset includes contrast-enhanced chest CT angiography data and contrast-enhanced abdominal CT angiography data. The contrast-enhanced chest CT angiography data comes from Jiangsu Provincial People's Hospital and the Pulmonary Artery Segmentation Challenge 2022. For images from Jiangsu Provincial People's Hospital, a PHILIPS Brilliance 256-slice CT scanner was used for acquisition, following standard protocols for contrast-enhanced chest CT scans. Image quality was manually verified, and all images were saved in DICOM format. DICOM images were converted to de-identified NIfTI images using SimpleITK, then the lung ROI was cropped, and vessel-enhanced images were obtained via the Frangi filter for storage. The contrast-enhanced abdominal images come from the Second Affiliated Hospital of Soochow University and the Kidney Parsing Challenge 2022. For images from the Second Affiliated Hospital of Soochow University, a GE Healthcare LightSpeed VCT 64-slice CT scanner was used for acquisition, following standard protocols for contrast-enhanced abdominal CT scans. Image quality was manually verified, and all images were saved in DICOM format. DICOM images were converted to de-identified NIfTI images using SimpleITK, then the kidney ROI was cropped and saved. Equipment Specifications: a. PHILIPS Brilliance 256-slice CT scanner; b. GE Healthcare LightSpeed VCT 64-slice CT scanner. Dataset Size: 9.1 GB.

搜集汇总

背景与挑战

背景概述

该数据集包含胸腹部增强CT血管图像，数据来源于江苏省人民医院、Pulmonary Artery Segmentation Challenge 2022挑战赛、苏州大学附属第二医院和Kidney PArsing Challenge2022挑战赛，使用专业CT设备采集并遵循标准扫描规范。图像经人工质量确认后，从DICOM格式转换为去除隐私信息的NIfTI格式，并进行了区域截取和血管增强处理，总数据量为9.1GB，共403个文件。