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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 6 | Month- June 2024
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Published Paper Details:
Paper Title
Harnessing 3D U-Net For Classifying Congenital Cardiovascular Diseases On Cardiac Images
Authors
Bensen Mathew, Rahul Ajith, Santa Mariam Saji, Bineetta Mary
Keywords
egmentation, Cardiac MRI, Classification, 3D U-Net.
Abstract
The deep learning technique, U-Net
architecture, are used to achieve accurate and
efficient segmentation of congenital heart vessels.
Congenital heart disease stands as a major cause of
mortality, affecting 1 in every 110 births. Timely
diagnosis through automatic cardiac segmentation is
crucial. Leveraging state-of-the-art neural network
architectures, our approach focuses on the
automated extraction and precise delineation of
intricate vascular structures within the heart. The
proposed methodology involves preprocessing the
data, training the deep learning model on a diverse
dataset, and fine-tuning the network to achieve
accurate segmentation results. By automating vessel
segmentation, our system contributes to expediting
diagnosis and treatment planning, ultimately
improving patient outcomes in the realm of
congenital heart diseases.
IJCRT's Publication Details
Unique Identification Number - IJCRT2406959
Paper ID - 255224
Page Number(s) - i518-i522
Pubished in - Volume 12 | Issue 6 | June 2024
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Bensen Mathew, Rahul Ajith, Santa Mariam Saji, Bineetta Mary, "Harnessing 3D U-Net For Classifying Congenital Cardiovascular Diseases On Cardiac Images", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 6, pp.i518-i522, June 2024, Available at :http://www.ijcrt.org/papers/IJCRT2406959.pdf
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Volume 12 | Issue 6
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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