Enhancement of medical images in an Atanassov's't intuitionistic fuzzy domain using an alternative intuitionistic fuzzy generator with application to image segmentation

被引:12
作者
Chaira, Tamalika [1 ]
机构
[1] Indian Inst Technol Delhi, Ctr Biomed Engn, New Delhi, India
关键词
Contrast enhancement; intuitionistic fuzzy set; hesitation degree; intuitionistic fuzzy entropy; segmentation; SETS; FUZZINESS; ENTROPY;
D O I
10.3233/IFS-131102
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a novel approach for intuitionistic fuzzy medical image enhancement using an alternative intuitionistic fuzzy generator and its advantage in segmentation for detecting/extracting abnormal lesions or blood vessels in medical images. The method constructs an intuitionistic fuzzy image using a proposed intuitionistic fuzzy generator that contains a parameter, 'lambda'. Optimal value of 'lambda' is obtained by maximizing intuitionistic fuzzy entropy. Then contrast intensifier is applied to the intuitionistic fuzzy image to obtain an enhanced image. The method shows an improved contrast of vaguely illuminated structures in medical images which has been proved quantitatively and experimentally. Also the enhanced image using the proposed method segments/extracts abnormal lesions or extracts blood vessels almost accurately. Experimental results show that the proposed method performs better than the existing non-fuzzy/fuzzy/Intuitionistic fuzzy methods with respect to enhancement and segmentation.
引用
收藏
页码:1347 / 1359
页数:13
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