AI Article Synopsis

  • The article surveys various segmentation methods in medical imaging, categorizing them by approach and application within the biomedical field.
  • It evaluates recent advancements in both semiautomated and automated segmentation techniques, highlighting their pros and cons, and discusses the role of computer-aided diagnosis (CAD) systems in enhancing radiology workflows.
  • The use of Picture Archiving Communication Systems (PACS) has shifted medical image interpretation from physical prints to digital formats, aiding quicker diagnoses through automatic segmentation that supports, rather than replaces, physician assessments.

Article Abstract

Rationale And Objectives: 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.

Materials And Methods: 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.

Results: By using PACS, the medical image interpretation may be changed from conventional hard-copy images to soft-copy studies viewed on the systems workstations.

Conclusion: The automatic segmentations assist the doctors in making quick diagnosis. The CAD need not be comparable to that of physicians, but is surely complementary.

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Source
http://dx.doi.org/10.1016/j.acra.2009.12.017DOI Listing

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