ANFIS based decision support system for prenatal detection of Truncus Arteriosus congenital heart defect |
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| Affiliation: | 1. Dhirajlal Gandhi College of Technology, Salem, Tamil Nadu, India;2. Muthayammal Engineering College, Rasipuram, Tamil Nadu, India;1. Laboratory of Structural Biology and Proteomics, Central Laboratories, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Brno, Czech Republic;2. Department of Cardiology, Austin Health, Australia;4. Department Pharmacology and Clinical Pharmacology, Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria;5. Central University Hospital of Asturias (HUCA), Oviedo, Spain;6. Centre for Chronic Disease (CCD), College of Health and Biomedicine Victoria University, Australia;1. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, PR China;2. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, PR China;3. School of Mechatronic Engineering and Automation, Shanghai University, 200072, PR China;1. Dpto. de Automatica y Computacion, Universidad Publica de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain;2. Institute of Smart Cities, Universidad Publica de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain;3. KERMIT, Dept. of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium |
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| Abstract: | 
Congenital Heart Disease or Defect (CHD) is one of the most crucial causes of neonatal mortality. According to the consensus reported by Cardiological society of India, CHD is responsible for around 10% of infant mortality in India. Clinical investigation of CHD is normally performed with ultrasound (US) imaging modality. It captures biological internal structures with improper boundary due to inherent speckle noise. The fetal heart particularly has thin wall chambers and hence this fact protrudes to be a main motivation to contrive a new Computer Aided Diagnostic Support System (CADSS) to diagnose prenatal CHD from US images. This proposed CADSS is the first framework implemented to diagnose the prenatal Truncus Arteriosus congenital heart defect (TACHD) from 2D US images. The system starts with pre-processing the clinical data-set utilizing Probabilistic Patch Based Maximum Likelihood Estimation (PPBMLE). Then the anatomical structures are highlighted from the pre-processed information, utilizing the Fuzzy Connectedness based image segmentation process. Then 32 diagnostic features are extracted by utilizing seven different feature extraction models. Amongst, a subset of potential features are selected by applying Fisher Discriminant Ratio (FDR) analysis. Finally, Adaptive Neuro Fuzzy Inference System (ANFIS) is built with the selected feature subset as classifier, to perceive and show clinical results of prenatal TACHD. The performance analysis of various classifiers is evaluated by using 10-fold cross validation process for the image data-set. Comparative results prove that the proposed classifier has the potential to produce the higher classification accuracy than existing classifiers. |
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| Keywords: | Congenital heart defects Truncus Arteriosus Computer aided diagnostic support system Fuzzy Connectedness Feature extraction ANFIS |
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