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Unsupervised segmentation of medical image based on difference of mutual information

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Abstract

In the scope of medical image processing, segmentation is important and difficult. There are still two problems which trouble us in this field. One is how to determine the number of clusters in an image and the other is how to segment medical images containing lesions. A new segmentation method called DDC, based on difference of mutual information (dMI) and pixon, is proposed in this paper. Experiments demonstrate that dMI shows one kind of intrinsic relationship between the segmented image and the original one and so it can be used to well determine the number of clusters. Furthermore, multi-modality medical images with lesions can be automatically and successfully segmented by DDC method.

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Correspondence to Chen Wufan.

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Lü, Q., Chen, W. Unsupervised segmentation of medical image based on difference of mutual information. SCI CHINA SER F 49, 484–493 (2006). https://doi.org/10.1007/s11432-006-0484-1

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  • DOI: https://doi.org/10.1007/s11432-006-0484-1

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