Cerebral artery segmentation

中风是导致死亡的主要原因之一
脑卒中是一种以脑血管病变为特征的脑血管疾病，如动脉狭窄和闭塞。准确评估脑血管病变对其诊断和治疗具有重要意义。磁共振血管造影(MRA)被广泛应用于脑血管树的可视化诊断。准确的冠状动脉MRA分割对脑血管疾病的定量分析，如程度的估计具有重要意义
考虑到大脑动脉的复杂网络存在显著的个体间差异，以及小血管中的微弱信号，即使对专家来说，分割也是具有挑战性的。飞行时间IICFI MRA是最广泛使用的非介入成像技术，可以在不使用造影剂的情况下描绘脑血管树的解剖结构。然而，具有良好标记的脑动脉的可访问的大规模TOF-MRA数据是有限的，这阻碍了可靠的自动脑动脉分割算法的开发和验证。
在这个挑战中，任务是艰巨的。对有症状性颅内动脉狭窄患者的三维TOF-MRA图像进行脑动脉的精确分割，有助于狭窄的识别和定量表征，有助于动脉硬化、夹层、动脉炎等血管疾病的诊断。烟雾病、可逆性脑血管收缩综合征等。

Stroke is one of the leading causes of death globally. Cerebral stroke is a cerebrovascular disease characterized by cerebrovascular lesions such as arterial stenosis and occlusion. Accurate assessment of such lesions is critical for the diagnosis and treatment of the disease. Magnetic Resonance Angiography (MRA) is widely utilized for the visual diagnosis of the cerebral vascular tree. Accurate segmentation of cerebral artery MRA images is of great significance for the quantitative analysis of cerebrovascular diseases, such as estimating lesion severity. Given the significant inter-individual variability in the complex network of cerebral arteries and the weak signals present in small blood vessels, segmentation tasks remain challenging even for medical experts. Time-of-Flight (TOF) MRA is the most widely used non-invasive imaging technique, which can delineate the anatomical structure of the cerebral vascular tree without the administration of contrast agents. However, accessible large-scale TOF-MRA datasets with well-annotated cerebral arteries are scarce, which impedes the development and validation of reliable automated cerebral artery segmentation algorithms. The task in this challenge is arduous. Accurate segmentation of cerebral arteries from 3D TOF-MRA images of patients with symptomatic intracranial arterial stenosis can help identify and quantitatively characterize stenosis, and assist in the diagnosis of vascular diseases including atherosclerosis, arterial dissection, arteritis, Moyamoya disease, and Reversible Cerebral Vasoconstriction Syndrome (RCVS), among others.

搜集汇总

背景与挑战

背景概述

该数据集专注于脑动脉分割，旨在通过三维TOF-MRA图像帮助诊断和定量分析脑血管疾病，如动脉狭窄和闭塞。数据集包含12.36MB的mask.zip文件，用于支持自动脑动脉分割算法的开发和验证。