Journal ArticleDOI
Medical image classification using genetic-algorithm based fuzzy-logic approach
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TLDR
The proposed genetic-algorithm-based fuzzy-logic approach is an effective method for computer-aided diagnosis in disease classification and achieves an average accuracy of 96% for myocardial heart disease and accuracy at 100% sensitivity level for microcalcification on mammograms.Abstract:
In this paper we present a genetic-algorithm-based fuzzy-logic approach for computer-aided diagnosis scheme in medical imaging. The scheme is applied to discriminate myocardial heart disease from echocardiographic images and to detect and classify clustered microcalcifications from mammograms. Unlike the conventional types of membership functions such as trapezoid, triangle, S curve, and singleton used in fuzzy reasoning, Gaussian-distributed fuzzy membership functions (GDMFs) are employed in the present study. The GDMFs are initially generated using various texture-based features obtained from reference images. Subsequently the shapes of GDMFs are optimized by a genetic-algorithm learning process. After optimization, the classifier is used for disease discrimination. The results of our experiments are very promising. We achieve an average accuracy of 96% for myocardial heart disease and accuracy of 88.5% at 100% sensitivity level for microcalcification on mammograms. The results demonstrated that our proposed genetic-algorithm-based fuzzy-logic approach is an effective method for computer-aided diagnosis in disease classification.read more
Citations
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Journal ArticleDOI
Image-Based Cardiac Diagnosis With Machine Learning: A Review.
Carlos Martín-Isla,Víctor M. Campello,Cristian Izquierdo,Zahra Raisi-Estabragh,Bettina Baeßler,Steffen E. Petersen,Steffen E. Petersen,Karim Lekadir +7 more
TL;DR: A thorough review of recent works in machine learning in cardiac imaging is presented and a detailed presentation of the machine learning methods that can be further exploited to enable more automated, precise and early diagnosis of most CVDs is presented.
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Ali Kalantari,Amirrudin Kamsin,Shahaboddin Shamshirband,Abdullah Gani,Hamid Alinejad-Rokny,Anthony T. Chronopoulos,Anthony T. Chronopoulos +6 more
TL;DR: The results show that Support Vector Machine and Artificial Immune Recognition System as a single based computational intelligence approach were the best methods in medical applications and the hybridization of SVM with other methods had great performances achieving better results in terms of accuracy, sensitivity and specificity.
A Review of Medical Image Segmentation: Methods and Available Software
Daniel Withey,Zoltan J. Koles +1 more
TL;DR: A representative set of methods that have been used for automatic medical image segmentation over the past 35 years are identified and an opportunity to view the transitions that have occurred as this research area has developed is provided.
Journal ArticleDOI
Medical image analysis for cancer management in natural computing framework
Sushmita Mitra,B. Uma Shankar +1 more
TL;DR: This survey highlights the role of natural computing, in efficiently analyzing radiographic medical images, for improved tumor management, and provides a categorization of the segmentation, feature extraction and selection methods, based on different natural computing technologies, with reference to the application.
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A fuzzy rule-based approach for characterization of mammogram masses into BI-RADS shape categories
A. Vadivel,B. Surendiran +1 more
TL;DR: Proposed approach is twice effective than existing Beamlet based features for classifying the mass as round, oval, lobular or irregular, and can be easily implemented and used in fuzzy inference system as if…then…else statements.
References
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Journal ArticleDOI
ROC methodology in radiologic imaging
TL;DR: This article develops ROC concepts in an intuitive way by identifying the fundamental issues that motivate ROC analysis and practical techniques for ROC data collection and data analysis.
Journal ArticleDOI
ROC analysis applied to the evaluation of medical imaging techniques.
TL;DR: This paper presents a brief description of the ROC, and shows how it provides a measure of diagnostic accuracy that is free of judgmental bias.
Journal ArticleDOI
Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps
Hiroyuki Yoshida,Janne J. Näppi +1 more
TL;DR: A 3-D computer-aided diagnosis scheme for automated detection of colonic polyps in computed tomography (CT) colonographic data sets was developed and its performance based on colonoscopy as the gold standard was evaluated.
Journal ArticleDOI
Improvement of radiologists' characterization of mammographic masses by using computer-aided diagnosis: an ROC study.
Heang Ping Chan,Berkman Sahiner,Mark A. Helvie,Nicholas Petrick,Marilyn A. Roubidoux,Todd E. Wilson,Dorit D. Adler,Chintana Paramagul,Joel S. Newman,Sethumadavan Sanjay-Gopal +9 more
TL;DR: CAD may be useful for assisting radiologists in classification of masses and thereby potentially help reduce unnecessary biopsies, as predicted from the improved ROC curves.
Journal ArticleDOI
Detection of breast masses in mammograms by density slicing and texture flow-field analysis
TL;DR: A method for the detection of masses in mammographic images that employs Gaussian smoothing and subsampling operations as preprocessing steps and methods for analyzing oriented flow-like textural information in mammograms are proposed.
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