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血细胞CAD:一种计算机辅助诊断软件工具,用于在显微镜图像中识别和表征血细胞

Rasoul Kasbgar¹, Alireza Vard²

¹Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan 81746, Iran; Student Research Committee, Isfahan University of Medical Sciences, Isfahan, Iran.

International journal of medical informatics

|March 11, 2025

概括

血细胞CAD软件在显微镜图像中自动检测和分类血细胞,帮助诊断多发性骨髓瘤癌症. 这种工具提高了病理学家的诊断效率和准确性.

科学领域:

医疗图像分析医学图像分析
计算病理学计算病理学
人工智能在诊断中的应用

背景情况:

传统的多发性骨髓瘤诊断依赖于病理学家手动显微镜检查血液样本.
这种手工工艺是劳动密集型,耗时,容易出现人为错误.
寻求自动化工具来提高血细胞检测和分类的效率和准确性.

研究的目的:

开发和评估PlasmaCell CAD,这是一个用于用于多发性骨髓瘤诊断的显微镜图像自动分析的软件工具.
通过自动化血细胞的检测,细分和分类来协助病理学家.
为改善癌症诊断提供一个可访问和用户友好的工具.

主要方法:

使用了面具R-CNN模型,增强了圆形转换,用于细胞检测和细分.
使用的支持矢量机 (SVM) 分类器,用于区分正常与异常的血细胞.
开发了一个图形用户界面 (GUI),用于直观的用户交互和工作流程.

主要成果:

在公共和本地数据集上证明了PlasmaCell CAD的有效性.
证实了软件在精确的血细胞细分和分类方面的能力.
强调了PlasmaCell CAD工具的用户友好性质和效率.

结论:

PlasmaCell CAD是一个免费可用的,可下载的Windows软件.
提供了一个用户友好的GUI与图像处理和可视化功能,以加快诊断.
呈现出有希望的结果,表明它对病理学家在诊断多发性骨髓瘤方面的实用性.

关键词:

循环转换转换循环转换深度学习 (Deep Learning) 是一种深度学习.图形用户界面 (GUI) 是指图形用户界面.细胞等离子体细胞

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