形态学的人工智能技术:机遇与前景

E.I. Ivanova, V.O. Grinin, A. Bakulina, P. S. Timashev
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引用次数: 0

摘要

在这项工作中,开发了一个基于U-Net和VGG神经网络架构的程序,用于分割和分析肾脏和结肠组织的扫描图像。该程序绘制了多达12类组织的解剖结构,还允许计算预测性组织学生物标志物,以支持医生的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ARTIFICIAL INTELLIGENCE TECHNOLOGIES FOR MORPHOLOGY: OPPORTUNITIES AND PROSPECTS
In this work, a program was developed based on U-Net and VGG neural network architectures for segmentation and analysis of scan images of kidney and colon tissues. The program maps up to 12 classes of anatomical structures in tissues, and also allows the calculation of predictive histological biomarkers to support physician decision-making.
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