Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/258561
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dc.coverage.spatialComputer Aided Decision Support System To Diagnose Prenatal Congenital Heart Defects From Ultrasound Images
dc.date.accessioned2019-09-18T12:34:21Z-
dc.date.available2019-09-18T12:34:21Z-
dc.identifier.urihttp://hdl.handle.net/10603/258561-
dc.description.abstractCongenital Heart Defect (CHD) is a birth defect formed during conception of the fetus. It is categorized into structural and functional heart defects. Approximately 33% to 50% of these defects are critical, requiring early intervention in the first year of neonatal life. Early diagnosis of prenatal CHD is a fundamental requirement in order to achieve a significant reduction in infant mortality rates. It is difficult for genuinely illustrating the hospital statistics for CHD in India, because countless of births happen at home in our nation with majority of it unsupervised by a qualified physician. Roughly 10% of present infant mortality in India is exclusively due to CHDs alone. In India Ultrasonography, Echocardiography and Color Doppler are being used as definitive tools for diagnosing prenatal CHD. The diverse merits of newlineUltrasound (US) modalities are the use of non-invasive imaging procedure with non-ionizing radiations, cost effectiveness, feature of providing pathologically significant diagnostic information and much more. The major drawback is the presence of inherent speckle noise, which makes the biological structures to appear with irregular boundaries. The major constraint in clinical radiology with manual investigation is the identification of diagnostically important sonographic markers. Diagnosing CHD from fetal heart 2 Dimensional (2D) US image requires unique set of progressive skills and exclusive exposure in anatomical structure identification of fetal heart. Owing to the nature of prenatal CHD diagnosis being a trivial and time consuming process, yet the diagnosis rate of prenatal CHD is low. newline newline
dc.format.extentxxiv, 157p.
dc.languageEnglish
dc.relationp.144-156
dc.rightsuniversity
dc.titleComputer aided decision support system to diagnose prenatal congenital heart defects from ultrasound images
dc.title.alternative
dc.creator.researcherSridevi S
dc.subject.keywordDiagnose Prenatal Congenital
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Interdisciplinary Applications
dc.subject.keywordHeart Defects
dc.subject.keywordUltrasound Images
dc.description.note
dc.contributor.guideNirmala S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2018
dc.date.awarded31/05/2018
dc.format.dimensions21 cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File24.15 kBAdobe PDFView/Open
02_certificates.pdf187.26 kBAdobe PDFView/Open
03_abstract.pdf10.31 kBAdobe PDFView/Open
04_acknowledgement.pdf14.49 kBAdobe PDFView/Open
05_table_of_contents.pdf149.15 kBAdobe PDFView/Open
06_list_of_symbols_and_abbreviations.pdf62.98 kBAdobe PDFView/Open
07_chapter1.pdf653.39 kBAdobe PDFView/Open
08_chapter2.pdf254.05 kBAdobe PDFView/Open
09_chapter3.pdf172.19 kBAdobe PDFView/Open
10_chapter4.pdf995.78 kBAdobe PDFView/Open
11_chapter5.pdf661.48 kBAdobe PDFView/Open
12_chapter6.pdf230 kBAdobe PDFView/Open
13_chapter7.pdf973.24 kBAdobe PDFView/Open
14_chapter8.pdf1.35 MBAdobe PDFView/Open
15_conclusion.pdf93.81 kBAdobe PDFView/Open
16_references.pdf136.96 kBAdobe PDFView/Open
17_list_of_publications.pdf86.39 kBAdobe PDFView/Open


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