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Review on 2D and 3D MRI Image Segmentation Techniques
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Background:
Magnetic Resonance Imaging is most widely used for early diagnosis
of abnormalities in human organs. Due to the technical advancement in digital image processing,
automatic computer aided medical image segmentation has been widely used in medical
diagnostics.
</P><P>
Discussion: Image segmentation is an image processing technique which is used for extracting image
features, searching and mining the medical image records for better and accurate medical diagnostics.
Commonly used segmentation techniques are threshold based image segmentation, clustering
based image segmentation, edge based image segmentation, region based image segmentation,
atlas based image segmentation, and artificial neural network based image segmentation.
Conclusion:
This survey aims at providing an insight about different 2-Dimensional and 3-
Dimensional MRI image segmentation techniques and to facilitate better understanding to the people
who are new in this field. This comparative study summarizes the benefits and limitations of
various segmentation techniques.
Bentham Science Publishers Ltd.
Title: Review on 2D and 3D MRI Image Segmentation Techniques
Description:
Background:
Magnetic Resonance Imaging is most widely used for early diagnosis
of abnormalities in human organs.
Due to the technical advancement in digital image processing,
automatic computer aided medical image segmentation has been widely used in medical
diagnostics.
</P><P>
Discussion: Image segmentation is an image processing technique which is used for extracting image
features, searching and mining the medical image records for better and accurate medical diagnostics.
Commonly used segmentation techniques are threshold based image segmentation, clustering
based image segmentation, edge based image segmentation, region based image segmentation,
atlas based image segmentation, and artificial neural network based image segmentation.
Conclusion:
This survey aims at providing an insight about different 2-Dimensional and 3-
Dimensional MRI image segmentation techniques and to facilitate better understanding to the people
who are new in this field.
This comparative study summarizes the benefits and limitations of
various segmentation techniques.
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