DETEKSI KEPALA JANIN PADA OBJEK TRANSTHALAMIC CITRA ULTRASONOGRAFI (USG) 2 DIMENSI (2D) MENGGUNAKAN METODE U-NET DAN FASTER R-CNN

MUBARAK, ALI and Erwin, Erwin (2022) DETEKSI KEPALA JANIN PADA OBJEK TRANSTHALAMIC CITRA ULTRASONOGRAFI (USG) 2 DIMENSI (2D) MENGGUNAKAN METODE U-NET DAN FASTER R-CNN. Undergraduate thesis, Sriwijaya University.

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Abstract

The head of the fetus is one part that is widely studied by experts because it has important information related to the health condition of the fetus. Research in the field of the fetal head requires a very long process and must be carried out with the help of competent medical personnel. One way that can be used to see the condition, development, and age of the fetus, can be done by detecting the fetal head, especially on trasnthalamic objects which are characterized by several factors, including the hyppocampal gyrus and thalami. There are various ways of detection algorithms, one of the algorithms that can be used is deep learning to accurately identify objects contained in the transthalamic. In this study, the fetal head detection process on transthalamic objects was segmented first using U-Net and continued with detection using Faster R-CNN. The results of this study obtained the best segmentation model in epoch 1000 and batch size 64, and the detection accuracy of Faster R-CNN mAP 89%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Kepala Janin, Deep Learning, U-Net, Faster R-CNN, Transthalamic.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > QA Mathematics > QA299.6-433 Analysis > Q334.A755 Artificial intelligence. Computational linguistics. Computer science. Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages R Medicine > R Medicine (General) > R856-857 Biomedical engineering. Electronics. Instrumentation > R857.M3.B56854 Biomedical materials. Stem cells--Therapeutic use. Regenerative medicine--Materials. TECHNOLOGY & ENGINEERING / Material Science. MEDICAL / Biotechnology R Medicine > R Medicine (General) > R856-857 Biomedical engineering. Electronics. Instrumentation > R857.N34.A37 Diagnostic imaging. Nanotechnology--Health aspects. Nanomedicine. Cancer--Treatment. TECHNOLOGY & ENGINEERING / Material Science
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Mr. Ali Mubarak
Date Deposited:	13 Sep 2022 07:36
Last Modified:	13 Sep 2022 07:36
URI:	http://repository.unsri.ac.id/id/eprint/78715

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