An Adaptive Region Growing based on Neutrosophic Set in Ultrasound Domain for Image Segmentation PDF Download
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Author: XUE JIANG
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11
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Book Description
Breast tumor segmentation in ultrasound is important for breast ultrasound (BUS) quantitative analysis and clinical diagnosis. Even this topic has been studied for a long time, it is still a challenging task to segment tumor in BUS accurately arising from difficulties of speckle noise and tissue background inconsistence. To overcome these difficulties, we formulate breast tumor segmentation as a classification problem in the neutrosophic set (NS) domain which has been previously studied for removing speckle noise and enhancing contrast in BUS images. The similarity set score and homogeneity value for each pixel have been calculated in the NS domain to characterize each pixel of BUS image. Based on that, the seed regions are selected by an adaptive Otsu-based thresholding method and morphology operations, then an adaptive region growing approach is developed for obtaining candidate tumor regions in NS domain.
Author: XUE JIANG
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11
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Book Description
Breast tumor segmentation in ultrasound is important for breast ultrasound (BUS) quantitative analysis and clinical diagnosis. Even this topic has been studied for a long time, it is still a challenging task to segment tumor in BUS accurately arising from difficulties of speckle noise and tissue background inconsistence. To overcome these difficulties, we formulate breast tumor segmentation as a classification problem in the neutrosophic set (NS) domain which has been previously studied for removing speckle noise and enhancing contrast in BUS images. The similarity set score and homogeneity value for each pixel have been calculated in the NS domain to characterize each pixel of BUS image. Based on that, the seed regions are selected by an adaptive Otsu-based thresholding method and morphology operations, then an adaptive region growing approach is developed for obtaining candidate tumor regions in NS domain.
Author: Jwan Najeeb Saeed
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 14
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Book Description
The most common cause of death among women globally is breast cancer. One of the key strategies to reduce mortality associated with breast cancer is to develop effective early detection techniques. The segmentation of breast ultrasound (BUS) image in Computer-Aided Diagnosis (CAD) systems is critical and challenging. Image segmentation aims to represent the image in a simplified and more meaningful way while retaining crucial features for easier analysis.
Author: Yanhui Guo
Publisher: Academic Press
ISBN: 0128181494
Category : Computers
Languages : en
Pages : 370
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Book Description
Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set’s novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. Introduces the mathematical model and concepts of neutrosophic theory and methods Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning Shows how NS techniques can be applied to medical image denoising, segmentation and classification Provides challenges and future directions in neutrosophic set based medical image analysis
Author: Dan Zhang
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 12
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Book Description
Clustering algorithm is one of the important research topics in the field of machine learning. Neutrosophic clustering is the generalization of fuzzy clustering and has been applied to many fields. this paper presents a new neutrosophic clustering algorithm with the help of regularization. Firstly, the regularization term is introduced into the FC-PFS algorithm to generate sparsity, which can reduce the complexity of the algorithm on large data sets. Secondly, we propose a method to simplify the process of determining regularization parameters. Finally, experiments show that the clustering results of this algorithm on artificial data sets and real data sets are mostly better than other clustering algorithms. Our clustering algorithm is effective in most cases.
Author: Yanhui Guo
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 19
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Book Description
This paper proposes novel skin lesion detection based on neutrosophic clustering and adaptive region growing algorithms applied to dermoscopic images, called NCARG. First, the dermoscopic images are mapped into a neutrosophic set domain using the shearlet transform results for the images.
Author: S. O. Haji
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 16
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Book Description
The thyroid nodule is one of the endocrine issues caused by an irregular cell development.This rate of survival can be improved by earlier nodule detection. Accordingly, the accurate recognition of the nodule is of the utmost importance in providing powerful results in building the survival rate.
Author: Bit, Arindam
Publisher: IGI Global
ISBN: 1522549706
Category : Medical
Languages : en
Pages : 388
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Book Description
Technological advancements in the last few decades have significantly revolutionized the healthcare industry, resulting in life expectancy improvement in human beings. The use of automated machines in healthcare has reduced human errors and has notably improved disease diagnosis efficiency. Design and Development of Affordable Healthcare Technologies provides emerging research on biomedical instrumentation, bio-signal processing, and device development within the healthcare industry. This book provides insight into various subjects including patient monitoring, medical imaging, and disease classification. This book is a vital reference source for medical professionals, biomedical engineers, scientists, researchers, and medical students interested in the comprehensive research on the advancements in healthcare technologies.
Author: DEEPIKA KOUNDAL
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 19
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Book Description
In medical science, diagnosis and prognosis is one of the most difficult and challenging task because of restricted subjectivity of the experts and presence of fuzziness in medical images. In observing the severity of several diseases, different professional experts may result in wrong diagnosis. In order to perform diagnosis intuitively in the medical images, different image processing methods have been explored in terms of neutrosophic theory to interpret the inherent uncertainty, ambiguity and vagueness. This paper demonstrates the use of neutrosophic theory in medical image denoising and segmentation where the performance is observed to be much better.
Author: Min Xian
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
Breast cancer is one of the leading causes of cancer death among women worldwide. In clinical routine, automatic breast ultrasound (BUS) image segmentation is very challenging and essential for cancer diagnosis and treatment planning.
Author: Geoff Dougherty
Publisher: Cambridge University Press
ISBN: 0521860857
Category : Computers
Languages : en
Pages : 463
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Book Description
Hands-on text for a first course aimed at end-users, focusing on concepts, practical issues and problem solving.
