Аннотирование объектов на медицинских изображениях рентгенографии грудной клетки с применением нейронных сетей; Современные технологии, экономика и образование
| Parent link: | Современные технологии, экономика и образование.— 2020.— [С. 235-238] |
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| मुख्य लेखक: | |
| निगमित लेखक: | |
| अन्य लेखक: | |
| सारांश: | Заглавие с титульного экрана Misinterpretation of X-ray images can lead to a worsening of the patient's condition. The purpose of this research was to develop an algorithm for automatic annotation of diseases on the X-ray image in order to improve the accuracy of the analysis of medical images. This paper considers various methods for solving the classification problem. During the research a database of annotated medical images of radiography was compiled. On this basis, a compactly connected convolutional neural network was trained and tested. The classification accuracy of developed algorithm is above 66% for 14 classes of diseases. |
| भाषा: | रूसी |
| प्रकाशित: |
2020
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| विषय: | |
| ऑनलाइन पहुंच: | http://earchive.tpu.ru/handle/11683/64713 |
| स्वरूप: | इलेक्ट्रोनिक पुस्तक अध्याय |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=632673 |
| सारांश: | Заглавие с титульного экрана Misinterpretation of X-ray images can lead to a worsening of the patient's condition. The purpose of this research was to develop an algorithm for automatic annotation of diseases on the X-ray image in order to improve the accuracy of the analysis of medical images. This paper considers various methods for solving the classification problem. During the research a database of annotated medical images of radiography was compiled. On this basis, a compactly connected convolutional neural network was trained and tested. The classification accuracy of developed algorithm is above 66% for 14 classes of diseases. |
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