甲状腺扫描图像数据集用于研究成人患者甲状腺病理
Benicio Grossling-Vallejos1,2, Carolina E Villegas Colmán1,2, Ronald Rivas1
1Universidad Nacional de Asunción, Instituto de Investigaciones en Ciencias de la Salud, San Lorenzo 111421, Paraguay.
Data in brief
|December 6, 2024
概括
这项研究引入了来自235名患者的641张甲状腺全息图像的新数据集,有助于甲状腺病理学分类的研究. 数据集包括各种条件,支持先进诊断算法的开发.
科学领域:
- 核医学就是核医学.
- 放射学 放射学是一门学科.
- 医疗成像医学成像
背景情况:
- 甲状腺病理需要准确的诊断工具.
- 现有的数据集可能缺乏多样性或用于训练AI模型的全面注释.
- 标准化采集协议对于可重复成像研究至关重要.
研究的目的:
- 为了呈现一种新的,精心策划的甲状腺 gammagraphy 图像数据集.
- 促进对甲状腺疾病的AI驱动分类算法的开发和验证.
- 为核医学专业人员和研究人员提供一个有价值的资源.
主要方法:
- 获得了来自235名成年患者的641张甲状腺血图图像 (2016-2024年).
- 使用了三模体SPECT-CT-PET设备 (MEDISO任何扫描SCP).
- 图像由核医学专业人员根据医生诊断进行分类.
主要成果:
- 一个包含各种甲状腺疾病的数据集,包括毒性腺瘤,喉 (扩散性,多节性,结节性),甲状腺切除术后的状态和甲状腺炎.
- 图像的详细分类为特定的病理实体和解剖变异.
- 图像是使用标准化协议获取的.
结论:
- 本文所介绍的数据集是推动甲状腺病理学领域人工智能的重要资源.
- 它支持研究甲状腺疾病的自动分类和诊断.
- 数据集的多样性和详细的注释将有助于提高诊断准确度.
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