Evaluation of the active contour and topographic watershed segmentation "assessment of the systolic ejection fraction in the left ventricular for medical assistance in 5D short axis cine MRI". Issue 11 (November 2020)

• Record Type: Journal Article
• Authors: Sakly, Houneida; Said, Mourad; Tagina, Moncef
• Is Part Of: Heliyon. Volume 6:Issue 11(2020)
• Publication Date: 2020-11
• Subjects: Computer science -- Engineering -- Cardiology -- Medical imaging -- Biomedical engineering -- Radiology -- Clinical research -- Contour segmentation -- Topographic watershed segmentation -- Short-axis 5D cardiac sequences -- MRI -- Medical decision making; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2020.e05547
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: A comparative study has been depicted between the contour and topographic watershed segmentation approach for short-axis 5D cardiac sequences with MRI for medical decision. The fifth dimension has been defined as the excitation of pixels based on the gray scale around the myocardium without consideration of the morphological structure of the heart in 3D and fourth dimension (time). Three patients were performed the first is healthy, the second has a genetic disease, and the third had a heart failure syndrome for a dimension ROI = 150mm, average age is 54 years old, and mean of weight = 86 kg. A contouring and watershed segmentation algorithm for a sample of 63 Cine Fiesta MRI sequences for short-axis cuts with Matlab and its in-box toolbox complements was implemented. For a healthy patient 13.4% tolerance rate for the estimation of the stroke fraction, 6.4% for a patient with genetic disease, 8.7% error rate for a patient with heart failure symptom. The results show that the regurgitation fraction by the contour approach for a patient case with symptom of the presence of a genetic disease is 0.0335% for an aortic valve, 0.248% for a mitral valve, an error rate 0.16% for estimating this parameter for the aortic orifice with the watershed segmentation approach. In return, for a patient with suspected heart failure (stenosis or regurgitation) the regurgitation fraction is estimated by 0% for aortic valve, 1.49 e + 03 % for a mitral valve, an error rate 11.76% compared to the watershed segmentation approach. The results are validated clinically. The Optimization of the topographic watershed approach with mutual information was simulated for the extraction of measurements (ejection fraction, regurgitation rate) within the left ventricle for three patient types (healthy, genetic pathology and heart failure). The results are considered interesting compared to the clinical assessment. Abstract : Computer science; Engineering; Cardiology; Medical imaging; Biomedical engineering; Radiology; Clinical research; Contour segmentation, Topographic watershed segmentation, Short-axis 5D cardiac sequences, MRI, Medical decision making.