Segmentasi 3D Kepala Janin Pada Citra USG Menggunakan U-NET. (Fetal Head 3D Segmentation in Ultrasound Images Using U-Net).

Jaya, Viko Adi (2023) Segmentasi 3D Kepala Janin Pada Citra USG Menggunakan U-NET. (Fetal Head 3D Segmentation in Ultrasound Images Using U-Net). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

The use of digital images has been utilized in various fields, including the medical field. One example is the use of digital images to detect the location of vital organs in the human body. The aim of this research is to generate a sliced shape of the fetal head area by applying deep learning segmentation methods and visualizing the results in a 3D model. The research stages involve the acquisition of ultrasound (USG) images, followed by image preprocessing to enhance the image quality for better segmentation results, and then the application of segmentation methods. The focus of this study is on the use of the U-Net method for fetal head segmentation in USG images and visualizing it in 3D. By employing the U-Net architecture in deep learning for 3D segmentation of the fetal head in USG images, this research is expected to provide more precise visualization results. The 3D segmentation of USG images can serve as a reference for obstetricians and other professionals for further research. From the implementation results, training was conducted on the Fetal Head dataset, achieving a training accuracy of 90.55%. Testing was also performed based on the model, and for the Fetal Head dataset, a performance of Intersection over Union (IoU) was reached at 87%. Based on the obtained results, the U-Net method can be used for fetal head segmentation in USG images.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Image Segmentation; USG Image; Fetal Head; U-Net Architecture; Image Preprocessing
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Program Studi Teknik Informatika
Depositing User:	1462000120 Viko Adi Jaya
Date Deposited:	17 Oct 2024 01:57
Last Modified:	17 Oct 2024 01:57
URI:	http://repository.untag-sby.ac.id/id/eprint/30908

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