Extraction of Whole-lung Field From Pseudo-chest X-ray Images Using U-net

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ファイル情報(添付)
タイトル
Extraction of Whole-lung Field From Pseudo-chest X-ray Images Using U-net
著者
細越 翔太
松尾 和明
収録物名
Shimane Journal of Medical Science
41
3
開始ページ 63
終了ページ 71
収録物識別子
ISSN 03865959
EISSN 24332410
内容記述
抄録・要旨
This study aimed to develop a model using U-net to extract the whole lung field from pseudo-chest X-ray images, including areas overlapping with cardiac and diaphragm shadows. Training involved pseudo-X-rays and lung label images from CT scans of 140 cases from the LIDC-IDRI dataset. The extraction performance of the model was evaluated using the Dice similarity coefficient (DSC). We also examined the correlations among patient size, lung volume, and DSC. As a result, the whole-lung field extraction model developed in this study tended to over-extract intestinal gas in some cases, and the extraction performance varied depending on the patient size. However, the DSC between the whole-lung label image and the output image was >0.9 for all the test data, indicating that the whole-lung field can be extracted from the pseudo chest X-ray image.
主題
computed tomography
chest X-ray image
whole-lung field
segmentation
deep learning
言語
英語
資源タイプ 紀要論文
出版者
Faculty of Medicine, Shimane University
島根大学医学部
発行日 2024-09
権利情報
Faculty of Medicine, Shimane University
権利関係(リンク) Creative Commons License
This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
出版タイプ Version of Record(出版社版。早期公開を含む)
アクセス権 オープンアクセス
関連情報
[NCID] AA00841586
[DOI] 10.51010/sjms.41.3_63