2015 2nd International Conference on Electronics and Communication Systems (ICECS) 2015
DOI: 10.1109/ecs.2015.7194713
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A spatial fuzzy based level set method for mammogram mass segmentation

Abstract: The evolution of level set segmentation needs an appropriate initialization and controlling parameters, which requires manual intervention. A new spatial fuzzy level set algorithm is proposed in this paper to facilitate the automatic mammogram image segmentation. The initial segmentation of the mass is obtained by spatial fuzzy clustering that incorporates the spatial information and local intensity information to compute the weighted summed image. The maximum membership cluster extracted from the fuzzy cluste… Show more

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Cited by 6 publications
(4 citation statements)
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References 17 publications
(21 reference statements)
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“…Fuzzy theory and fuzzy logic are well-known to be flexible tools where imprecise knowledge or not-well defined features have to be used [17]. It has been extensively used in system control domain and applied in image processing to some extent [18][19][20][21]. In the past 10 years, thresholding segmentation approaches have been proposed based on fuzzy logic and fuzzy calculations.…”
Section: Related Workmentioning
confidence: 99%
“…Fuzzy theory and fuzzy logic are well-known to be flexible tools where imprecise knowledge or not-well defined features have to be used [17]. It has been extensively used in system control domain and applied in image processing to some extent [18][19][20][21]. In the past 10 years, thresholding segmentation approaches have been proposed based on fuzzy logic and fuzzy calculations.…”
Section: Related Workmentioning
confidence: 99%
“…After scanning the body, the radiologist will analyze the medical image to get the diagnosis. The analysis process can run using the help of computer programs to speed up and improve the accuracy of the diagnostic process [3]. In the field of medical image analysis on bioinformatics science, one of the computational processes that can always be improved to help this work is image segmentation [4].…”
Section: Introductionmentioning
confidence: 99%
“…If in previous studies [9] fuzzy logic with spatial information applied to brain MRI imagery, Dr. J. Dinesh Peter applied to the image of the mammogram used for the story of breast cancer [3]. The study utilized mammogram image data from mini-MIAS database then comparison was done between standard method of FCM and FCM with new spatial information.…”
Section: Introductionmentioning
confidence: 99%
“…D. Pereira et al [7], implemented an artifact removal algorithm in CC and MLO views, the wavelet transform and Wiener filter are used for image enhancement, finally, the authors employed multiple thresholding wavelet transform and genetic algorithm for masses detection and segmentation. J. Anitha et al [8], proposed spatial based fuzzy level set algorithm for automatic mammogram mass segmentation, the output of fuzzy clustering is used as input for the level set segmentation that is used to refine the mass boundary, the results of fuzzy clustering are used to estimate the control parameters of level set algorithm. Khaddouj Taifi et al [9], proposed a hybrid technique for enhancing mammograms, this technique combines Nonsubsampled Contourlet Transform and Hommomorphic Filtering, then the authors presented a comparative study based on three different algorithms: proposed methods, homomorphic filtering and unsharp masking, the experimental results of this study show that the proposed method significantly reduces noise in high noise mammograms.…”
Section: Introductionmentioning
confidence: 99%