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Review on 2D and 3D MRI Image Segmentation Techniques.

S Shirly1, K Ramesh1

  • 1Department of Computer Applications, Anna University Regional-Campus, Tirunelveli, Tamil Nadu, India.

Current Medical Imaging Reviews
|January 25, 2020
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Summary

This survey reviews 2D and 3D Magnetic Resonance Imaging (MRI) segmentation techniques for early abnormality diagnosis. It compares various methods, highlighting their benefits and limitations for medical image analysis.

Keywords:
2-dimensional3- dimensional image segmentationMagnetic resonance imagingimage processingimage segmentation

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Biomedical Engineering

Background:

  • Magnetic Resonance Imaging (MRI) is crucial for early diagnosis of human organ abnormalities.
  • Advancements in digital image processing have led to the widespread use of automatic computer-aided medical image segmentation in diagnostics.

Purpose of the Study:

  • To provide an overview of 2-Dimensional and 3-Dimensional MRI image segmentation techniques.
  • To facilitate understanding for newcomers to the field of medical image segmentation.
  • To summarize the advantages and disadvantages of various segmentation methods.

Main Methods:

  • Review and comparison of common segmentation techniques including threshold-based, clustering-based, edge-based, region-based, atlas-based, and artificial neural network-based methods.
  • Analysis of both 2D and 3D MRI image segmentation approaches.

Main Results:

  • Different segmentation techniques offer varying levels of accuracy and efficiency for medical image analysis.
  • Each method presents unique benefits and limitations that influence its applicability in specific diagnostic scenarios.

Conclusions:

  • Understanding the diverse MRI segmentation techniques is essential for accurate medical diagnostics.
  • This comparative study aids in selecting appropriate segmentation methods based on their strengths and weaknesses.