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Early Detection of Lung Cancer by Artificial Neural Network and Fuzzy Inference System
http://hdl.handle.net/10458/6102
http://hdl.handle.net/10458/6102590f47a2-5dcf-434c-9643-391da861e0a1
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文 (1.2 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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| 公開日 | 2020-06-21 | |||||
| タイトル | ||||||
| タイトル | Early Detection of Lung Cancer by Artificial Neural Network and Fuzzy Inference System | |||||
| 言語 | ja | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | ANFIS, CAD, False Detection Rate, Hybrid Learning | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| 著者 |
Khaing, Zin Htwe
× Khaing, Zin Htwe× YAMAMORI, Kunihito× Katayama, Tetsuro× Tin, Mar Kyi |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Over the past few years, a great number of attempts have been made to decrease the death rate of lung cancer. Recent reports showed the early diagnosis of lung cancer by screening programs is one way to reduce lung cancer mortality. Moreover, radiological examination consists of a large number of images per patient that leads to the manual diagnosis with being consumed much time and energy of radiologists. Computer-aided Detection (CAD) in radiology can provide a functional and advantageous way to physicians aiming to improve accuracy and to assist in early detection of cancer, and to save the time of radiologists in exam evaluation. Using given input/output data values, the proposed ANFIS can build mapping based on both human knowledge (fuzzy if-then rules form) and hybrid learning algorithm. In our proposed work, both image processing techniques and ANFIS have been employed to reduce false detection rate and to get more efficient and accurate CAD system. | |||||
| 言語 | en | |||||
| 書誌情報 |
ja : 宮崎大学工学部紀要 en : Memoirs of Faculty of Engineering, University of Miyazaki 巻 46, p. 321-326, 発行日 2016-07-31 |
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| 出版者 | ||||||
| 出版者 | 宮崎大学工学部 | |||||
| 言語 | ja | |||||
| 出版者 | ||||||
| 出版者 | Faculty of Engineering, University of Miyazaki | |||||
| 言語 | en | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 05404924 | |||||
| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA00732558 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
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Khaing, Zin Htwe, YAMAMORI, Kunihito, Katayama, Tetsuro, Tin, Mar Kyi, 2016, Early Detection of Lung Cancer by Artificial Neural Network and Fuzzy Inference System: 宮崎大学工学部, 321–326 p.
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