| Item type |
文献 / Documents(1) |
| 公開日 |
2022-08-23 |
| アクセス権 |
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|
アクセス権 |
open access |
| 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 |
journal article |
| 出版社版DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1155/2021/6651175 |
|
|
言語 |
ja |
|
|
関連名称 |
10.1155/2021/6651175 |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| タイトル |
|
|
タイトル |
Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography |
|
言語 |
en |
| 著者 |
長澤, 利彦
タブチ, ヒトシ
マスモト, ヒロキ
モリタ, ショウジ
仁木, 昌徳
オオハラ, ザイゲン
ヨシズミ, ユキ
三田村, 佳典
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Purpose. The present study aimed to compare the accuracy of diabetic retinopathy (DR) staging with a deep convolutional neural network (DCNN) using two different types of fundus cameras and composite images. Method. The study included 491 ultra-wide-field fundus ophthalmoscopy and optical coherence tomography angiography (OCTA) images that passed an image-quality review and were graded as no apparent DR (NDR; 169 images), mild nonproliferative DR (NPDR; 76 images), moderate NPDR (54 images), severe NPDR (90 images), and proliferative DR (PDR; 102 images) by three retinal experts by the International Clinical Diabetic Retinopathy Severity Scale. The findings of tests 1 and 2 to identify no apparent diabetic retinopathy (NDR) and PDR, respectively, were then assessed. For each verification, Optos, OCTA, and Optos OCTA imaging scans with DCNN were performed. Result. The Optos, OCTA, and Optos OCTA imaging test results for comparison between NDR and DR showed mean areas under the curve (AUC) of 0.79, 0.883, and 0.847; sensitivity rates of 80.9%, 83.9%, and 78.6%; and specificity rates of 55%, 71.6%, and 69.8%, respectively. Meanwhile, the Optos, OCTA, and Optos OCTA imaging test results for comparison between NDR and PDR showed mean AUC of 0.981, 0.928, and 0.964; sensitivity rates of 90.2%, 74.5%, and 80.4%; and specificity rates of 97%, 97%, and 96.4%, respectively. Conclusion. The combination of Optos and OCTA imaging with DCNN could detect DR at desirable levels of accuracy and may be useful in clinical practice and retinal screening. Although the combination of multiple imaging techniques might overcome their individual weaknesses and provide comprehensive imaging, artificial intelligence in classifying multimodal images has not always produced accurate results. |
|
言語 |
en |
| 書誌情報 |
en : Journal of Ophthalmology
巻 2021,
p. 6651175,
発行日 2021-04-05
|
| 収録物ID |
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収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2090004X |
| 収録物ID |
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収録物識別子タイプ |
ISSN |
|
収録物識別子 |
20900058 |
| 出版者 |
|
|
出版者 |
Hindawi |
|
言語 |
en |
| 権利情報 |
|
|
言語 |
en |
|
権利情報 |
This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| EID |
|
|
識別子 |
386840 |
|
識別子タイプ |
URI |
| 言語 |
|
|
言語 |
eng |
jo_2021_6651175.pdf (8.92 MB)
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