JOURNAL ARTICLE

Image decomposition based ultrasound image segmentation by using fuzzy clustering

Abstract

Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.

Keywords:
Artificial intelligence Image segmentation Segmentation-based object categorization Scale-space segmentation Pattern recognition (psychology) Image texture Computer vision Cluster analysis Speckle noise Computer science Region growing Segmentation Speckle pattern Minimum spanning tree-based segmentation Preprocessor Range segmentation

Metrics

10
Cited By
0.31
FWCI (Field Weighted Citation Impact)
18
Refs
0.67
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 and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence

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