التفاصيل البيبلوغرافية
| العنوان: |
Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| المؤلفون: |
Yuzhen Ding, Jason M. Holmes, Hongying Feng, Baoxin Li, Lisa A. McGee, Jean-Claude M. Rwigema, Sujay A. Vora, William W. Wong, Daniel J. Ma, Robert L. Foote, Samir H. Patel, Wei Liu |
| المصدر: |
Communications Medicine, Vol 4, Iss 1, Pp 1-10 (2024) |
| بيانات النشر: |
Nature Portfolio, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Medicine |
| مصطلحات موضوعية: |
Medicine |
| الوصف: |
Abstract Background In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging (OBI) is unavailable. However, tumor visibility is constrained due to the projection of patient’s anatomy onto a 2D plane, potentially leading to substantial setup errors. In treatment room with 3D-OBI such as cone beam CT (CBCT), the field of view (FOV) of CBCT is limited with unnecessarily high imaging dose. A solution to this dilemma is to reconstruct 3D CT from kV images obtained at the treatment position. Methods We propose a dual-models framework built with hierarchical ViT blocks. Unlike a proof-of-concept approach, our framework considers kV images acquired by 2D imaging devices in the treatment room as the solo input and can synthesize accurate, full-size 3D CT within milliseconds. Results We demonstrate the feasibility of the proposed approach on 10 patients with head and neck (H&N) cancer using image quality (MAE: 97%) and patient position uncertainty (shift error: |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2730-664X |
| Relation: |
https://doaj.org/toc/2730-664X |
| DOI: |
10.1038/s43856-024-00672-y |
| URL الوصول: |
https://doaj.org/article/b76a854caba441a88fc17eb6c0163323 |
| رقم الانضمام: |
edsdoj.b76a854caba441a88fc17eb6c0163323 |
| قاعدة البيانات: |
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