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DETEKSI ABNORMALITAS STRUKTUR JANTUNG ANAK DENGAN METODE MASK REGION CONVOLUTIONAL NEURAL NETWORK

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Penilaian

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Detecting abnormal heart structures in infant is an important issue in the field of medicine. One method that can be used to detect abnormal heart structures in children is by using the Mask Region Convolutional Neural Network (Mask-RCNN) method. The process of training MRCNN in detecting abnormal heart structures in children can be done by utilizing well-segmented and labeled heart image datasets. After training is done, Mask-RCNN can be used to detect abnormal heart structures in heart images that have never been seen before.. The best Performance achieved in the segmentation of 7 heart structures was a DSC of 82.40%, an IoU of 70.43%, and an mAP of 90.79%. In the segmentation of 7 heart chambers and the septum, the best Performance achieved was 79.08% for DSC, 67.69% for IoU, and 89.60% for mAP. For the segmentation of Holes, the best model Performance on the 4CH data was 81.35%, 57.41%, and 89.9% for DSC, IoU, and mAP respectively. On the 5CH data, it was 79.23%, 65.72%, and 91.08%. For the Long Axis data, it was 80.13%, 48.98%, and 89.27%. For the Short Axis data, it was 72.83%, 56.32%, and 86.15%. Finally, for the Subcostal data, it was 76.42%, 60.72%, and 88.64% for each parameter of DSC, IoU, and mAP.By using the Mask-RCNN method, detection of abnormal heart structure in infants can be done accurately and efficiently. This method can help doctors in diagnosing and treating cases of abnormal heart structure in infants more quickly and accurately.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307001608	T96865	T968652023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T968652023

Publisher

Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiv, 106 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem Pakar
Jurusan Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

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