Evaluasi Kualitas Citra Ultrasonografi Janin Menggunakan Unsupervised Image-to-Image Translation Networks. (Evaluation Of Fetal Ultrasound Image Quality Using Unsupervised Image-To-Image Translation Networks).

Atikah, Atikah (2024) Evaluasi Kualitas Citra Ultrasonografi Janin Menggunakan Unsupervised Image-to-Image Translation Networks. (Evaluation Of Fetal Ultrasound Image Quality Using Unsupervised Image-To-Image Translation Networks). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

Evaluate and improve the quality of fetal ultrasound (USG) images using method Unsupervised Image-to-Image Translation Networks. Fetal ultrasound images are often influenced by various factors such as the position of the fetus, the quality of the ultrasound equipment, and the condition of the pregnant woman, which can reduce the clarity and visual quality of the image. By utilizing unsupervised artificial neural network techniques, this research develops a model that can improve the quality of ultrasound images automatically. Evaluation is carried out by comparing the original image and the repaired image using several image quality metrics. The results of this study indicate that the use of Unsupervised Image-to-Image Translation Networks is not effective in improving the quality of fetal ultrasound images. Inconsistent metric values require further development in the evaluation approach used.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ultrasound Image, UNIT, Evaluation Image
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Program Studi Teknik Informatika
Depositing User:	1462000163 Atikah Atikah
Date Deposited:	06 Sep 2001 15:36
Last Modified:	06 Oct 2001 15:07
URI:	http://repository.untag-sby.ac.id/id/eprint/35128

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