Nugroho, Hanung Adi and Frannita, Eka Legya and Nurfauzi, Rizki (2021) An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet. In: International Conference on Electrical Engineering, Computer Science and Informatics (EECSI).
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Abstract
Recently, some countries have been distressing with the increasing number of thyroid cancer cases. The number of cases is increased every year. Practically, one of the causes of the increase in the number of patients was due to manual examination. Recently, some researchers have involved in the development of CAD to solve this problem. However, CAD itself still has some limitations. One of the major limitations is that the nodules segmentation process was not well-conducted. Thus, to overcome that problem, we proposed a scheme for detecting and segmenting the thyroid nodules. Our scheme consisted of four major steps which were data augmentation process, normalization process, segmentation and evaluation process. The proposed scheme was tested in 480 thyroid ultrasound images. The proposed scheme successfully achieved more than 90 in all evaluation metrics in both detection and segmentation process. According to this achievement, we concluded that our proposed method had potential to be integrated as part of the intelligent system for detecting and segmenting thyroid cancer. © 2021 Institute of Advanced Engineering and Science (IAES).
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Cited by: 2 |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
Depositing User: | Sri JUNANDI |
Date Deposited: | 25 Oct 2024 03:48 |
Last Modified: | 25 Oct 2024 03:48 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/8635 |