PENGGUNAAN CONVOLUTION NEURAL NETWORK (CNN) DENGAN ARSITEKTUR U-NET DAN FASTER R-CNN DALAM MENDETEKSI TRANSCEREBELLAR PADA KEPALA JANIN DARI CITRA ULTRASONOGRAFI 2 DIMENSI

SYAHPUTRA, MUHAMMAD RIZKY RASYID and Erwin, Erwin (2022) PENGGUNAAN CONVOLUTION NEURAL NETWORK (CNN) DENGAN ARSITEKTUR U-NET DAN FASTER R-CNN DALAM MENDETEKSI TRANSCEREBELLAR PADA KEPALA JANIN DARI CITRA ULTRASONOGRAFI 2 DIMENSI. Undergraduate thesis, Sriwijaya University.

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Abstract

The head of the fetus is an important part to determine the condition of the fetus in pregnant women. Detection of the fetal head requires a long process and also takes a lot of time. This detection process also requires expertise and experience that must be carried out by a specialist in the field of obstetrics. This is a challenge to determine the condition of the fetus, especially detecting objects that are in the transcerebellar part. Objects that become markers on the transcerebellar are Cerebellar Hemi and Cisterna Magna. Therefore, in this study, the process of designing an algorithm with a deep learning method will be carried out to detect objects that are in trancerebellar in medical images to get accurate object results. This study performs segmentation using the U-Net architecture and will continue with the detection process using the Faster R-CNN architecture. The best results obtained are in the 3rd model using epoch 1000 and batch size 64 in segmentation and getting an mAP of 87.3% at the time of detection.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Kepala Janin, Deep learning, U-Net, Faster R-CNN, Transcerbellar.
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. Muhammad Rizky Rasyid Syahputra
Date Deposited:	13 Sep 2022 07:50
Last Modified:	13 Sep 2022 07:50
URI:	http://repository.unsri.ac.id/id/eprint/78722

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