Prediction of Tetralogy of Fallot using Fuzzy Clustering

2020 ◽  
Vol 13 (4) ◽  
pp. 694-705
Author(s):  
K.R. Kosala Devi ◽  
V. Deepa
Keyword(s):  
Heart Disease ◽  
Tetralogy Of Fallot ◽  
Jaccard Index ◽  
Local Information ◽  
Rand Index ◽  
Image Clustering ◽  
Adjusted Rand Index ◽  
Clustering Methods ◽  
Fuzzy C Means ◽  
Pixel Value

Background: Congenital Heart Disease is one of the abnormalities in your heart's structure. To predict the tetralogy of fallot in a heart is a difficult task. Cluster is the collection of data objects, which are similar to one another within the same group and are different from the objects in the other clusters. To detect the edges, the clustering mechanism improve its accuracy by using segmentation, Colour space conversion of an image implemented in Fuzzy c-Means with Edge and Local Information. Objective: To predict the tetralogy of fallot in a heart, the clustering mechanism is used. Fuzzy c-Means with Edge and Local Information gives an accuracy to detect the edges of a fallot to identify the congential heart disease in an efficient way. Methods: One of the finest image clustering methods, called as Fuzzy c-Means with Edge and Local Information which will introduce the weights for a pixel value to increase the edge detection accuracy value. It will identify the pixel value within its local neighbor windows to improve the exactness. For evaluation , the Adjusted rand index metrics used to achieve the accurate measurement. Results: The cluster metrics Adjusted rand index and jaccard index are used to evaluate the Fuzzy c- Means with Edge and Local Information. It gives an accurate results to identify the edges. By evaluating the clustering technique, the Adjusted Rand index, jaccard index gives the accurate values of 0.2, 0.6363, and 0.8333 compared to other clustering methods. Conclusion: Tetralogy of fallot accurately identified and gives the better performance to detect the edges. And also it will be useful to identify more defects in various heart diseases in a accurate manner. Fuzzy c-Means with Edge and Local Information and Gray level Co-occurrence matrix are more promising than other Clustering Techniques.

COMPARATIVE STUDY OF CLUSTERING ALGORITHMS IN ORDER TO VIRTUAL HISTOLOGY (VH) IMAGE SEGMENTATION

2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Zahra Rezaei ◽  
Mohd Daud Kasmuni ◽  
Ali Selamat ◽  
Mohd Shafry Mohd Rahim ◽  
Golnoush Abaei ◽  
...  
Keyword(s):  
Human Error ◽  
Color Image ◽  
Clustering Algorithms ◽  
Image Clustering ◽  
Clustering Methods ◽  
Color Code ◽  
Virtual Histology ◽  
Fuzzy C Means ◽  
Geometrical Features ◽  
Nonhierarchical Clustering

Atherosclerosis is the deadliest type of heart disease caused by soft or “vulnerable” plaque (VP) formation in the coronary arteries.  Recently, Virtual Histology (VH) has been proposed based on spectral analysis of Intravascular Ultrasound (IVUS) provides color code of coronary tissue maps. Based on pathophysiological studies, obtaining information about existence and extension of confluent pool’s component inside plaque is important. In addition, plaque components’ localization respect to the luminal border has major role in determining plaque vulnerability and plaque–stent interaction. Computational methods were applied to prognostic the pattern's structure of each component inside the plaque. The first step for post-processing of VH methodology to get further information of geometrical features is segmentation or decomposition. The medical imaging segmentation field has developed to assist cardiologist and radiologists and reduce human error in recent years as well. To perform color image clustering, several strategies can be applied which include traditional hierarchical and nonhierarchical. In this paper, we applied and compared four nonhierarchical clustering methods consists of Fuzzy C-means (FCM), Intuitionistic Fuzzy C-means (IFCM), K-means and SOM artificial neural networks in order to automate segmentation of the VH-IVUS images.  

Mechanical-electrical interaction of the right ventricle in patients with repaired tetralogy of fallot: the next step towards resynchronization in congenital heart disease

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Rodriguez Garcia ◽  
A Pijuan Domenech ◽  
J Perez Rodon ◽  
B Benito Villabriga ◽  
J Francisco Pascual ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ejection Fraction ◽  
Right Ventricle ◽  
Tetralogy Of Fallot ◽  
Negative Correlation ◽  
Electrical Activation ◽  
Basal Region ◽  
Repaired Tetralogy Of Fallot ◽  
The Right ◽  
Activation Delay

Abstract Introduction Patients with repaired tetralogy of Fallot (rTF) and severe pulmonary regurgitation frequently progress to dilation and dysfunction of the right ventricle (RV). It has been documented in the literature that there is a correlation between the duration of the QRS in the surface electrocardiogram and the hemodynamic parameters of the RV of these patients, suggesting the presence of a mechanical-electrical interaction. Purpose To determine if there is an association between the contraction delay in certain areas of the RV measured in M-mode echocardiography and the delay in electrical activation measured in the electroanatomic map (EAM) of RV in patients with rTF. Methods Unicentric and observational study of all patients with rTF undergoing EAM, echocardiography with study of RV asynchrony and cardiac magnetic resonance imaging (MRI). Activation delay in the antero-basal area and in the RV outflow tract (RVOT) in the EAM were both analysed (Figure 1A). The shortening delay in the same areas in M-mode echocardiography was also evaluated (Figure 1B, C). MRI data regarding volume and ejection fraction was also collected. Results 64 patients were included (36.7±10.6 years, 65% men). The mean total activation time of the RV (RV-TAT) was 127.3±42.4 ms. Activation mapping showed a recurrent pattern with beginning in the interventricular septum and ending in RV antero-basal region and/or RVOT. A linear positive correlation was observed between RV-TAT and the activation delay in both regions analysed (ρ=0.60 and ρ=0.52, respectively; p<0.001) and also between the electrical and mechanical delay in the anterior wall (ρ=0.41; p=0.001). On the other hand, it was observed a negative correlation between RV ejection fraction (RVEF), measured on MRI, and the RV-TAT (ρ=−0.41, p=0.002) and also between RVEF and the activation delay in the RV antero-basal region and in the RVOT (ρ=−0.32, p=0.016 and ρ=−0.36, p=0.007, respectively). Conclusions There is a mechanical-electrical interaction in the RV of patients with rTF, with a negative correlation between the activation delay and RVEF and between mechanical and electrical activation delay in specific anatomical regions (regional mechanical-electrical interaction). These results may guide future studies on resynchronization in this heart disease. Figure 1. EAM and echocardiographic measures Funding Acknowledgement Type of funding source: None

Endothelial function state following repair of cyanotic congenital heart diseases

2013 ◽  
Vol 25 (2) ◽  
pp. 222-227 ◽  
Author(s):  
Mohammad Reza Sabri ◽  
Hooman Daryoushi ◽  
Mojgan Gharipour
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Endothelial Function ◽  
Tetralogy Of Fallot ◽  
Congenital Heart ◽  
Cyanotic Congenital Heart Disease ◽  
Vascular Endothelial ◽  
Vascular Endothelial Function ◽  
Flow Mediated Dilatation ◽  
The Mean

AbstractBackgroundRepairing cyanotic congenital heart disease may be associated with preserving endothelial function. The present study aimed to evaluate vascular endothelial function in patients with repaired cyanotic congenital heart disease.MethodsIn a case–control study conducted in 2012 in Isfahan, Iran, 42 consecutive patients aged <35 years who had suffered from different types of cyanotic congenital heart disease and had undergone complete repair of their congenital heart defect were assessed in regard to their endothelial function state by measuring flow-mediated dilatation and other cardiac function indices. They were paired with 42 sex- and age-matched healthy controls.ResultsThe mean flow-mediated dilatation was lower in patients with repaired cyanotic congenital heart disease than in the controls [6.14±2.78 versus 8.16±1.49 respectively (p<0.001)]. Significant adverse correlations were found between flow-mediated dilatation, age, and body mass indexes, in those who underwent repair surgery. In addition, flow-mediated dilatation had a positive association with the shortening fraction, ejection fraction, and tricuspid annular plane systolic excursion value, and it was also inversely associated with carotid intima-media thickness and the myocardial performance index. The mean of the flow-mediated dilatation was significantly higher in the group with tetralogy of Fallot along with complete repair before the age of 2.5 years and also in those patients with total anomalous pulmonary venous connection or transposition of the great arteries repaired with an arterial switch operation before 6 months of age, compared with the other two subgroups. This includes patients with a tetralogy of Fallot defect repaired after 4 years of age and those with complex cyanotic congenital heart disease that was repaired after 2.5 years of age (mean age at repair 9±6.1 years).ConclusionEarly repair of a cyanotic defect can result in the protection of vascular endothelial function and prevent the occurrence of vascular accidents at an older age.

scholarly journals Order Selection in Unsupervised Learning and Clustering for Arbitrary and Non-Arbitrary Shaped Data

2021 ◽  
Author(s):  
Mahdi Shahbaba
Keyword(s):  
Objective Function ◽  
Unsupervised Learning ◽  
Minimum Spanning Tree ◽  
Statistical Testing ◽  
Adjusted Rand Index ◽  
Order Selection ◽  
Clustering Methods ◽  
Conventional Methods ◽  
Anderson Darling ◽  
Statistical Testing Method

This thesis focuses on clustering for the purpose of unsupervised learning. One topic of our interest is on estimating the correct number of clusters (CNC). In conventional clustering approaches, such as X-means, G-means, PG-means and Dip-means, estimating the CNC is a preprocessing step prior to finding the centers and clusters. In another word, the first step estimates the CNC and the second step finds the clusters. Each step having different objective function to minimize. Here, we propose minimum averaged central error (MACE)-means clustering and use one objective function to simultaneously estimate the CNC and provide the cluster centers. We have shown superiority of MACEmeans over the conventional methods in term of estimating the CNC with comparable complexity. In addition, on average MACE-means results in better values for adjusted rand index (ARI) and variation of information (VI). Next topic of our interest is order selection step of the conventional methods which is usually a statistical testing method such as Kolmogrov-Smrinov test, Anderson-Darling test, and Hartigan's Dip test. We propose a new statistical test denoted by Sigtest (signature testing). The conventional statistical testing approaches rely on a particular assumption on the probability distribution of each cluster. Sigtest on the other hand can be used with any prior distribution assumption on the clusters. By replacing the statistical testing of the mentioned conventional approaches with Sigtest, we have shown that the clustering methods are improved in terms of having more accurate CNC as well as ARI and VI. Conventional clustering approaches fail in arbitrary shaped clustering. Our last contribution of the thesis is in arbitrary shaped clustering. The proposed method denoted by minimum Pathways is Arbitrary Shaped (minPAS) clustering is proposed based on a unique minimum spanning tree structure of the data. Our simulation results show advantage of minPAS over the state-of-the-art arbitrary shaped clustering methods such as DBSCAN and Affinity Propagation in terms of accuracy, ARI and VI indexes.

scholarly journals A Bi-directional Fuzzy C-Means Clustering Ensemble Algorithm Considering Local Information

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Chunhua Ren ◽  
Linfu Sun
Keyword(s):  
Clustering Algorithms ◽  
Real Data ◽  
Local Information ◽  
Data Sets ◽  
Clustering Ensemble ◽  
K Nearest Neighbors ◽  
Fuzzy C Means ◽  
Clustering Quality ◽  
Fuzzy C Means Clustering ◽  
Fcm Clustering

AbstractThe classic Fuzzy C-means (FCM) algorithm has limited clustering performance and is prone to misclassification of border points. This study offers a bi-directional FCM clustering ensemble approach that takes local information into account (LI_BIFCM) to overcome these challenges and increase clustering quality. First, various membership matrices are created after running FCM multiple times, based on the randomization of the initial cluster centers, and a vertical ensemble is performed using the maximum membership principle. Second, after each execution of FCM, multiple local membership matrices of the sample points are created using multiple K-nearest neighbors, and a horizontal ensemble is performed. Multiple horizontal ensembles can be created using multiple FCM clustering. Finally, the final clustering results are obtained by combining the vertical and horizontal clustering ensembles. Twelve data sets were chosen for testing from both synthetic and real data sources. The LI_BIFCM clustering performance outperformed four traditional clustering algorithms and three clustering ensemble algorithms in the experiments. Furthermore, the final clustering results has a weak correlation with the bi-directional cluster ensemble parameters, indicating that the suggested technique is robust.

scholarly journals Pattern of congenital heart disease among children presenting to the Uganda Heart Institute, Mulago Hospital: a 7-year review

2020 ◽  
Vol 20 (2) ◽  
pp. 745-752 ◽  
Author(s):  
Judith Namuyonga ◽  
Sulaiman Lubega ◽  
Twalib Aliku ◽  
John Omagino ◽  
Craig Sable ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Tetralogy Of Fallot ◽  
Congenital Heart ◽  
Heart Defects ◽  
Truncus Arteriosus ◽  
Deletion Syndrome ◽  
Mulago Hospital ◽  
22Q11.2 Deletion ◽  
Heart Institute

Background: Congenital heart disease (CHD) is the most common congenital anomaly in children. Over half of the deaths due to CHD occur in the neonatal period. Most children with unrepaired complex heart lesions do not live to celebrate their first birthday. We describe the spectrum of congenital heart disease in Uganda. Methods: We retrospectively reviewed the data of children with CHD who presented to the Uganda Heart Institute (UHI), Mulago Hospital Complex from 2007 to 2014. Results: A total of 4621 children were seen at the UHI during the study period. Of these, 3526 (76.3%) had CHD; 1941(55%) were females. Isolated ventricular septal defect (VSD) was the most common CHD seen in 923 (27.2%) children followed by Patent ductus arteriosus (PDA) 760 (22%) and atrial septal defects (ASD) 332 (9.4%). Tetralogy of Fallot (TOF) and Truncus arteriosus were the most common cyanotic heart defects (7% and 5% respectively). Dysmorphic features were diagnosed in 185 children, of which 61 underwent genetic testing (Down syndrome=24, 22q11.2 deletion syndrome n=10). Children with confirmed 22q11.2 deletion had conotruncal abnormalities. Conclusion: Isolated VSD and Tetralogy of Fallot are the most common acyanotic and cyanotic congenital heart defects. We report an unusually high occurrence of Truncus arteriosus. Keywords: Congenital heart disease; children; Uganda.

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