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. 2010 Jan;35(1):3-14.
doi: 10.4103/0971-6203.58777.

Automated medical image segmentation techniques

Neeraj Sharma  1 , Lalit M Aggarwal
Affiliations

Automated medical image segmentation techniques

Neeraj Sharma et al. J Med Phys. 2010 Jan.

Abstract

Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

Keywords: Artificial intelligence techniques; computed tomography; magnetic resonance imaging; medical images artifacts; segmentation.

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Conflict of interest statement

Conflict of Interest: None declared.

Figures

Figure 1
Figure 1
Artifacts in MR Imaging
Figure 2
Figure 2
Examples of CT Artifacts: (A) Streak (B) Motion (C) Beam-hardening (D-E) Ring (F) Bloom [4]
Figure 3
Figure 3
Image Histogram (three peaks separated by two minima)
Figure 4a
Figure 4a
Original Abdomen CT Image
Figure 4b
Figure 4b
Segmentation of Abdomen (CT image using threshold technique)
Figure 5
Figure 5
Result of Edge-based Segmentation of Abdomen (CT image)
Figure 6
Figure 6
Segmentation of Abdomen (CT image using region based technique)
Figure 7
Figure 7
Individual Segments of Brain CT Image (A) Original (B-E) Individual segments (F) Segmented image in Pseudo Color
See this image and copyright information in PMC

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