PENDETEKSIAN PENDARAHAN PADA CITRA DIGITAL RADIOLOGI OTAK MANUSIA MENGGUNAKAN FASTER REGION-BASED CONVOLUTIONAL NEURAL NETWORK

ARTAMANANDA, ARTAMANANDA and Fachrurrozi, Muhammad and Darmawahyuni, Annisa (2023) PENDETEKSIAN PENDARAHAN PADA CITRA DIGITAL RADIOLOGI OTAK MANUSIA MENGGUNAKAN FASTER REGION-BASED CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

This research discusses four scenarios in developing a Faster Region-based Convolutional Neural Network (Faster R-CNN) model to detect bleeding in radiological images of the human brain. We specifically tested and compared key parameters, namely learning rate, batch size, backbone architecture, and data sharing, to determine the most effective configuration. The results show that the learning rate 0.001, batch size 4, ResNet-50 backbone and data split 90:10 are the best of the datasets used. These findings could provide a valuable basis for the development of more sophisticated medical detection applications, with the hope of improving the diagnosis and treatment of brain hemorrhage sufferers more effectively.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Pendarahan, Deep Learning, Informatika Medis
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Artamananda Artamananda
Date Deposited:	28 Nov 2023 01:48
Last Modified:	28 Nov 2023 01:48
URI:	http://repository.unsri.ac.id/id/eprint/131234

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