JOURNAL ARTICLE

A novel level set method for medical image segmentation

Soumen BiswasRanjay Hazra

Year: 2019 Journal:   2019 IEEE Region 10 Symposium (TENSYMP) Pages: 237-242

Abstract

A new level set method is proposed to segment medical images by introducing intensity inhomogeneity and a double well potential function. First of all, an adaptive weighted median filter (AWMF) is used to define the region with respect to intensity inhomogeneity. Then, the analysis is performed by incorporating an energy function with intensity inhomogeneity-free images. Thereafter a new double well potential function is introduced that reduces the computational time. Finally, segmentation is performed on medical images by minimizing the overall energy function. The experimental results show the robustness of the proposed method in comparison to the existing methods in terms of computational time and Jaccard Index (JI).

Keywords:
Jaccard index Robustness (evolution) Image segmentation Level set (data structures) Computer science Segmentation Intensity (physics) Level set method Image (mathematics) Energy (signal processing) Function (biology) Artificial intelligence Set (abstract data type) Filter (signal processing) Medical imaging Computer vision Algorithm Pattern recognition (psychology) Mathematics Statistics Optics

Metrics

2
Cited By
0.21
FWCI (Field Weighted Citation Impact)
15
Refs
0.57
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
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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