Angelou0516/ACOUSLIC-AI

ACOUSLIC-AI（低收入国家中与操作者无关的胎儿腹围超声测量）是一个用于MICCAI 2024挑战赛的数据集，专注于从超声图像中测量胎儿腹围。数据集包含300个3D体积超声图像和对应的分割掩码，每个文件约335MB，总大小约200GB。数据格式为MetaImage (.mha)，分割掩码包含背景、最佳平面（胎儿腹部）和次优平面的标注。此外，还提供了一个CSV文件，包含腹围测量数据。数据集支持的任务包括胎儿腹部分割、腹围测量和超声图像分析。ACOUSLIC-AI (Abdominal Circumference Operator-agnostic UltraSound measurement in Low-Income Countries) is a dataset for the MICCAI 2024 challenge focused on fetal abdominal circumference measurement from ultrasound images. The dataset contains 300 3D volumetric ultrasound images and corresponding segmentation masks, each file approximately 335MB, totaling ~200GB. The data format is MetaImage (.mha), with segmentation masks including background, optimal plane (fetal abdomen), and suboptimal plane annotations. Additionally, a CSV file with abdominal circumference measurements is provided. The dataset supports tasks such as fetal abdomen segmentation, abdominal circumference measurement, and ultrasound image analysis.

搜集汇总

背景与挑战

背景概述

ACOUSLIC-AI是一个用于胎儿腹部超声图像分割和周长测量的医学影像数据集，包含300个图像和掩码文件，总大小约200GB。该数据集来自MICCAI 2024挑战赛，专注于低收入国家的超声测量应用，适用于图像分割和医学分析任务。