JOURNAL ARTICLE

Medical Image Segmentation Methods, Algorithms, and Applications

Abstract

Medical images have made a great impact on medicine, diagnosis, and treatment. The most important part of image processing is image segmentation. Many image segmentation methods for medical image analysis have been presented in this paper. In this paper, we have described the latest segmentation methods applied in medical image analysis. The advantages and disadvantages of each method are described besides examination of each algorithm with its application in Magnetic Resonance Imaging and Computed Tomography image analysis. Each algorithm is explained separately with its ability and features for the analysis of grey-level images. In order to evaluate the segmentation results, some popular benchmark measurements are presented in the final section.

Keywords:
Computer science Image segmentation Artificial intelligence Segmentation Scale-space segmentation Segmentation-based object categorization Computer vision Image processing Image (mathematics) Benchmark (surveying) Medical imaging Region growing Pattern recognition (psychology) Algorithm

Metrics

319
Cited By
11.57
FWCI (Field Weighted Citation Impact)
101
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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