Apeejay College of Engineering, ICE Department, Sohna, Gurgaon, India.
Acad Radiol. 2010 May;17(5):658-71. doi: 10.1016/j.acra.2009.12.017. Epub 2010 Mar 7.
This article provides a survey of segmentation methods for medical images. Usually, classification of segmentation methods is done based on the approaches adopted and the domain of application.
This survey is conducted on the recent segmentation methods used in biomedical image processing and explores the methods useful for better segmentation. A critical appraisal of the current status of semiautomated and automated methods is made for the segmentation of anatomical medical images emphasizing the advantages and disadvantages. Computer-aided diagnosis (CAD) used by radiologists as a second opinion has become one of the major research areas in medical imaging and diagnostic radiology. A picture archiving communication system (PACS) is an integrated workflow system for managing images and related data that is designed to streamline operations throughout the whole patient care delivery process.
By using PACS, the medical image interpretation may be changed from conventional hard-copy images to soft-copy studies viewed on the systems workstations.
The automatic segmentations assist the doctors in making quick diagnosis. The CAD need not be comparable to that of physicians, but is surely complementary.
本文对医学图像分割方法进行了综述。通常，分割方法的分类是基于所采用的方法和应用领域进行的。
本调查针对生物医学图像处理中使用的最新分割方法，并探索了有助于更好分割的方法。对半自动化和自动化方法的当前状态进行了批判性评估，重点介绍了解剖医学图像分割的优缺点。放射科医生作为第二意见使用的计算机辅助诊断 (CAD) 已成为医学成像和诊断放射学的主要研究领域之一。图片存档与通信系统 (PACS) 是一个用于管理图像和相关数据的集成工作流程系统，旨在简化整个患者护理交付过程中的操作。
通过使用 PACS，医学图像解释可以从传统的硬拷贝图像更改为在系统工作站上查看的软拷贝研究。
自动分割有助于医生快速诊断。CAD 不一定与医生的诊断能力相当，但肯定是互补的。
