A new 2.5 D representation for lymph node detection in CT (CT Lymph Nodes)

This collection consists of Computed Tomography (CT) images of the mediastinum and abdomen in which lymph node positions are marked by radiologists at the National Institutes of Health, Clinical Center. Radiologists at the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory labeled a total of 388 mediastinal lymph nodes in CT images of 90 patients and a total of 595 abdominal lymph nodes in 86 patients. The collection is aimed at the medical image computing community for developing and assessing computer-aided detection methods. Automated detection of lymph nodes can be an important clinical diagnostic tool but is very challenging due to the low contrast of surrounding structures in CT and to their varying sizes, poses, shapes and sparsely distributed locations. This data set is made available to make direct comparison to other detection methods in order to advance the state of the art.本数据集收录了纵隔与腹部的计算机断层扫描（Computed Tomography，CT）图像，图像中淋巴结的位置已由美国国立卫生研究院临床中心的放射科医师标注完成。影像生物标志物与计算机辅助诊断实验室的放射科医师共计完成如下标注工作：对90例患者的CT图像中的388枚纵隔淋巴结，以及86例患者的CT图像中的595枚腹部淋巴结进行了标注。本数据集面向医学图像计算领域的研究者，用于开发与评估计算机辅助检测算法。自动淋巴结检测可成为极具临床价值的诊断工具，但受限于CT图像中淋巴结周围组织结构对比度较低，且淋巴结尺寸、空间姿态、形态各异且分布稀疏等因素，该任务极具挑战性。本数据集公开发布，旨在为各类检测算法提供统一的直接对比基准，以推动领域技术前沿的发展。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于CT图像中淋巴结检测的医学影像集合，包含来自176名患者的纵隔和腹部CT图像，其中由放射科医生标记了983个淋巴结位置（388个纵隔淋巴结和595个腹部淋巴结）。它旨在为医学图像计算社区提供资源，以开发和评估计算机辅助检测方法，并促进与其他方法的直接比较，以应对淋巴结检测在低对比度、多变大小和稀疏分布方面的挑战。