基于胸部CT图像的肺部疾病分类 - - 综述
Shri Ramtej Kondamuri1, Venkata Sainath Gupta Thadikemalla1, Gunnam Suryanarayana1
1Department of ECE, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, Andhra Pradesh, 520007, India.
Current medical imaging
|February 23, 2024
概括
这项研究分析了从CT扫描中分类肺部疾病的方法,突出了深度学习.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 肺部病理学 肺部病理学
背景情况:
- 计算机断层扫描 (CT) 扫描对于诊断肺部疾病至关重要.
- 手动解释CT扫描可能导致诊断错误.
- 需要先进的系统来准确地从CT图像中分类肺部疾病.
研究的目的:
- 通过CT扫描,对使用CT扫描进行肺部疾病分类的不同方法进行广泛分析.
- 引导研究人员开发先进的诊断系统.
- 审查当前的机器学习 (ML) 技术及其在该领域的表现.
主要方法:
- 肺部疾病诊断和治疗程序的概述.
- 现有的肺病分类方法的描述.
- 基于ML的肺病分类的一般程序的解释.
- 对肺部疾病分类的ML近期进展的审查.
主要成果:
- 深度学习技术在彻底改变早期肺部疾病识别方面显著有前途.
- 介绍了各种方法及其性能的分析.
- 讨论了用于肺部疾病分类的ML技术的现有挑战.
结论:
- 深度学习显著提高了早期肺部疾病的检测.
- 这项工作旨在提高医疗专业人员对肺部疾病的认识和分类能力.
- 进一步开发先进的ML系统对于准确及时诊断至关重要.
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