An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet
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 deve...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/280429/1/An_Automated_Detection_and_Segmentation_of_Thyroid_Nodules_using_Res-UNet.pdf |
| _version_ | 1826050424843534336 |
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| author | Nugroho, H.A. Frannita, E.L. Nurfauzi, R. |
| author_facet | Nugroho, H.A. Frannita, E.L. Nurfauzi, R. |
| author_sort | Nugroho, H.A. |
| collection | UGM |
| description | 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). |
| first_indexed | 2024-03-14T00:03:46Z |
| format | Conference or Workshop Item |
| id | oai:generic.eprints.org:280429 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:03:46Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2804292023-11-28T09:00:26Z https://repository.ugm.ac.id/280429/ An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet Nugroho, H.A. Frannita, E.L. Nurfauzi, R. Other Information and Computing Sciences Medical Biotechnology Oncology and Carcinogenesis Cancer Diagnosis Information System 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). 2021 Conference or Workshop Item PeerReviewed application/pdf en https://repository.ugm.ac.id/280429/1/An_Automated_Detection_and_Segmentation_of_Thyroid_Nodules_using_Res-UNet.pdf Nugroho, H.A. and Frannita, E.L. and Nurfauzi, R. (2021) An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet. In: 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI). https://ieeexplore.ieee.org/document/9624248 |
| spellingShingle | Other Information and Computing Sciences Medical Biotechnology Oncology and Carcinogenesis Cancer Diagnosis Information System Nugroho, H.A. Frannita, E.L. Nurfauzi, R. An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title | An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title_full | An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title_fullStr | An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title_full_unstemmed | An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title_short | An Automated Detection and Segmentation of Thyroid Nodules using Res-UNet |
| title_sort | automated detection and segmentation of thyroid nodules using res unet |
| topic | Other Information and Computing Sciences Medical Biotechnology Oncology and Carcinogenesis Cancer Diagnosis Information System |
| url | https://repository.ugm.ac.id/280429/1/An_Automated_Detection_and_Segmentation_of_Thyroid_Nodules_using_Res-UNet.pdf |
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