Pituitary Tumor MRI Segmentation Dataset

Pituitary adenoma (PA) is one of the most common tumors of the central nervous system, accounting for about 10%-25% of all cases. Although it is generally considered to be a benign tumor, the tumor can compress important tissue structures around it and cause corresponding symptoms. And surgical treatment is the preferred treatment for pituitary adenoma. Therefore, preoperative observation on MRI is important to provide anatomical information to plan the resection and predict the prognosis. However, due to the lack of MRI annotation data of pituitary adenoma, there are limited studies on MRI automatic segmentation of pituitary adenoma through deep learning.

垂体腺瘤（Pituitary adenoma, PA）是中枢神经系统最常见的肿瘤之一，约占所有中枢神经系统肿瘤病例的10%~25%。尽管该肿瘤通常被归类为良性病变，但仍可压迫周围重要组织结构并引发相应临床症状。手术治疗是垂体腺瘤的首选治疗方案。因此，术前磁共振成像（Magnetic Resonance Imaging, MRI）检查对于获取解剖学信息以规划手术切除、预测患者预后具有重要意义。然而，由于垂体腺瘤的MRI标注数据相对匮乏，基于深度学习实现垂体腺瘤MRI自动分割的相关研究较为有限。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于垂体腺瘤MRI分割的医学影像数据集，包含55例3D T1加权对比增强脑部MRI图像及手动标注的二进制掩码，由中山大学第一附属医院回顾性收集。数据集旨在支持深度学习研究，解决垂体腺瘤自动分割中标注数据不足的问题，适用于术前规划和预后预测。