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LiTS 数据集介绍 - 知乎
LiTS (The Liver Tumor Segmentation Benchmark) 是专注于肝脏及其肿瘤分割的 CT 数据集。该数据集收集了 7 个不同医学中心的数据，包含 131 例训练集和 70 例测试集。
Awesome-Medical-Dataset resources LiTS. md at main - GitHub
LiTS (The Liver Tumor Segmentation Benchmark) is a CT dataset focused on the segmentation of the liver and its tumors The dataset compiles data from 7 different medical centers, comprising 131 training cases and 70 test cases
LiTS2017数据集介绍、下载与预处理 - CSDN博客
LiTS (The Liver Tumor Segmentation Benchmark) 是专注于肝脏及其肿瘤分割的 CT 数据集。该数据集收集了 7 个不同医学中心的数据，包含 131 例训练集和 70 例测试集，其中测试数据标签不公开。
LiTS|医学图像分析数据集|肿瘤分割数据集
LiTS（Liver Tumor Segmentation Challenge）数据集是由MICCAI（Medical Image Computing and Computer Assisted Intervention Society）在2017年发起的一项国际挑战赛。该数据集的构建旨在推动肝脏及肝脏肿瘤的自动分割技术的发展，特别是在计算机辅助诊断（CAD）和医学影像分析领域。
Library, Information, and Technology Services | LITS
Welcome to LITS: Library, Information, and Technology Services Your place to do research, find library materials and get technology support
LiTS28_数据集-飞桨AI Studio星河社区
LiTS医疗图像分割作为全球顶级医学影像AI挑战赛，是由慕尼黑理工大学、以色列特拉维夫大学等高校、科研院所与国际医学影像分析顶级年会MICCAI联合举办。
LiTS17 - eva - kaiko-ai. github. io
The LiTS dataset can be downloaded from the official LiTS competition page The training split comes into two zip files, namely Training_Batch1 zip and Training_Batch2 zip, which should be extracted and merged
The Liver Tumor Segmentation Benchmark (LiTS) - ScienceDirect
The LiTS evaluation of MICCAI 2018 was integrated into MSD and attracted much attention, receiving 18 valid submissions Methods were ranked according to two metrics: Dice score and ASD (in liver and liver tumor segmentation tasks)
LiTS 数据集预处理（一）肝脏肿瘤图像分割 - CSDN博客
在LiTS数据集中，CT图像的分割掩膜（mask）通常是由医学专家手动标注的。掩膜中每个像素的值代表不同的结构或区域，例如肝脏、肿瘤或背景。
GitHub - assassint2017 MICCAI-LITS2017: liver segmentation using deep . . .
Liver tumor Segmentation Challenge (LiTS) contain 131 contrast-enhanced CT images provided by hospital around the world 3DIRCADb dataset is a subset of LiTS dataset with case number from 27 to 48 we train our model with 111 cases from LiTS after removeing the data from 3DIRCADb and evaluate on 3DIRCADb dataset