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PIMedSeg: 渐进式交互式医疗图像细分技术

Xun Gong¹, Li Wang¹, Longlong Miao²

¹School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, PR China; Engineering Research Center of Sustainable Urban Intelligent Transportation, Ministry of Education, Chengdu 611756, PR China; Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu 611756, PR China.

Computer methods and programs in biomedicine

|August 31, 2023

概括

本研究介绍了一种交互式医疗图像细分框架,该框架使用最小的用户输入来获得高质量的结果. 渐进式工作流大大减少了对细分任务的手工工作量.

关键词:

边缘的涂边缘的涂交互式细分化交互式细分化地区点击点击点击点击变压器变压器变压器

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科学领域:

医学成像分析医学成像分析
计算机视觉在医疗保健中的应用
生物医学工程生物医学工程

背景情况:

准确的医学图像细分对于诊断至关重要,但自动化方法仍然具有挑战性.
交互式细分为克服全自动化方法的局限性提供了一个有希望的替代方案.
现有的交互式方法往往需要大量的用户努力.

研究的目的:

提出一个新的交互式细分框架.
为了减少用户的努力,同时实现高质量的细分结果.
为了提高医疗图像细分的效率.

主要方法:

一个渐进的工作流,包含用户提供的区域点击和边缘涂.
使用新的磁盘和曲线转换来编码用户输入.
采用基于变压器的模块来改进功能,集成CNN输出和输入地图.

主要成果:

在各种医学成像模式中证明了有效性,包括超声波 (美国),CT和MRI.
在实验中超越了最先进的替代细分方法.
在用户互动最小的情况下实现了高质量的细分.

结论:

拟议的框架为高质量的医疗图像细分提供了可行的解决方案.
显著减少了大量手动细分工作的需要.
提供了用户交互和细分精度之间的平衡.