Iterative relative fuzzy connectedness and object definition: theory, algorithms, and applications in image segmentation

2002 ◽  
Author(s):  
P.K. Saha ◽  
J.K. Udupa
Keyword(s):  
Image Segmentation ◽  
Fuzzy Connectedness

Fuzzy connectedness and image segmentation

2003 ◽  
Vol 91 (10) ◽  
pp. 1649-1669 ◽  
Author(s):  
J.K. Udupa ◽  
P.K. Saha
Keyword(s):  
Image Segmentation ◽  
Fuzzy Connectedness

Medical Image Mining Using Fuzzy Connectedness Image Segmentation

2016 ◽  
pp. 184-209
Author(s):  
Amol P. Bhagat ◽  
Mohammad Atique
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Image Feature ◽  
Image Mining ◽  
Imaging Data ◽  
Dicom Image ◽  
Fuzzy Connectedness ◽  
Geometric Moments ◽  
Novel Approach ◽  
Minimum Number

This chapter presents novel approach fuzzy connectedness image segmentation with geometric moments (FCISGM) for digital imaging and communications in medicine (DICOM) image mining. As most of the medical imaging data is exchanged in DICOM format, this chapter focuses on the various methodologies available for DICOM image feature extraction and mining. The comparison of existing medical image mining approaches with the proposed FCISGM approach is provided in this chapter. After carrying out exhaustive results it has been found that proposed FCISGM method gives more precise results and requires minimum number of computations compare to other medical image mining approaches resulting in improved relevant outcomes.

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