139 related articles for article (PubMed ID: 37883678)
1. Extensive clinical testing of Deep Learning Segmentation models for thorax and breast cancer radiotherapy planning.
Mikalsen SG; Skjøtskift T; Flote VG; Hämäläinen NP; Heydari M; Rydén-Eilertsen K
Acta Oncol; 2023 Oct; 62(10):1184-1193. PubMed ID: 37883678
[TBL] [Abstract][Full Text] [Related]
2. Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery.
Chung SY; Chang JS; Choi MS; Chang Y; Choi BS; Chun J; Keum KC; Kim JS; Kim YB
Radiat Oncol; 2021 Feb; 16(1):44. PubMed ID: 33632248
[TBL] [Abstract][Full Text] [Related]
3. Clinical evaluation of deep learning-based automatic clinical target volume segmentation: a single-institution multi-site tumor experience.
Hou Z; Gao S; Liu J; Yin Y; Zhang L; Han Y; Yan J; Li S
Radiol Med; 2023 Oct; 128(10):1250-1261. PubMed ID: 37597126
[TBL] [Abstract][Full Text] [Related]
4. Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system.
Costea M; Zlate A; Durand M; Baudier T; Grégoire V; Sarrut D; Biston MC
Radiother Oncol; 2022 Dec; 177():61-70. PubMed ID: 36328093
[TBL] [Abstract][Full Text] [Related]
5. A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.
Marschner S; Datar M; Gaasch A; Xu Z; Grbic S; Chabin G; Geiger B; Rosenman J; Corradini S; Niyazi M; Heimann T; Möhler C; Vega F; Belka C; Thieke C
Radiat Oncol; 2022 Jul; 17(1):129. PubMed ID: 35869525
[TBL] [Abstract][Full Text] [Related]
6. Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process.
Duan J; Bernard M; Downes L; Willows B; Feng X; Mourad WF; St Clair W; Chen Q
Med Phys; 2022 Apr; 49(4):2570-2581. PubMed ID: 35147216
[TBL] [Abstract][Full Text] [Related]
7. Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer.
Almberg SS; Lervåg C; Frengen J; Eidem M; Abramova TM; Nordstrand CS; Alsaker MD; Tøndel H; Raj SX; Wanderås AD
Radiother Oncol; 2022 Aug; 173():62-68. PubMed ID: 35618100
[TBL] [Abstract][Full Text] [Related]
8. Geometric and dosimetric evaluation of atlas based auto-segmentation of cardiac structures in breast cancer patients.
Kaderka R; Gillespie EF; Mundt RC; Bryant AK; Sanudo-Thomas CB; Harrison AL; Wouters EL; Moiseenko V; Moore KL; Atwood TF; Murphy JD
Radiother Oncol; 2019 Feb; 131():215-220. PubMed ID: 30107948
[TBL] [Abstract][Full Text] [Related]
9. Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.
Choi MS; Choi BS; Chung SY; Kim N; Chun J; Kim YB; Chang JS; Kim JS
Radiother Oncol; 2020 Dec; 153():139-145. PubMed ID: 32991916
[TBL] [Abstract][Full Text] [Related]
10. Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.
Qiu W; Zhang W; Ma X; Kong Y; Shi P; Fu M; Wang D; Hu M; Zhou X; Dong Q; Zhou Q; Zhu J
Med Phys; 2023 Jan; 50(1):284-296. PubMed ID: 36047281
[TBL] [Abstract][Full Text] [Related]
11. Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region.
Kieselmann JP; Kamerling CP; Burgos N; Menten MJ; Fuller CD; Nill S; Cardoso MJ; Oelfke U
Phys Med Biol; 2018 Jul; 63(14):145007. PubMed ID: 29882749
[TBL] [Abstract][Full Text] [Related]
12. The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.
Guo H; Wang J; Xia X; Zhong Y; Peng J; Zhang Z; Hu W
Radiat Oncol; 2021 Jun; 16(1):113. PubMed ID: 34162410
[TBL] [Abstract][Full Text] [Related]
13. Atlas Sampling for Prone Breast Automatic Segmentation of Organs at Risk: The Importance of Patients' Body Mass Index and Breast Cup Size for an Optimized Contouring of the Heart and the Coronary Vessels.
Wang X; Miralbell R; Fargier-Bochaton O; Bulling S; Vallée JP; Dipasquale G
Technol Cancer Res Treat; 2020; 19():1533033820920624. PubMed ID: 32314647
[TBL] [Abstract][Full Text] [Related]
14. Initial Evaluation of a Novel Cone-Beam CT-Based Semi-Automated Online Adaptive Radiotherapy System for Head and Neck Cancer Treatment - A Timing and Automation Quality Study.
Yoon SW; Lin H; Alonso-Basanta M; Anderson N; Apinorasethkul O; Cooper K; Dong L; Kempsey B; Marcel J; Metz J; Scheuermann R; Li T
Cureus; 2020 Aug; 12(8):e9660. PubMed ID: 32923257
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.
Wang J; Chen Y; Xie H; Luo L; Tang Q
Sci Rep; 2022 Aug; 12(1):13650. PubMed ID: 35953516
[TBL] [Abstract][Full Text] [Related]
16. Clinical evaluation of deep learning and atlas-based auto-segmentation for critical organs at risk in radiation therapy.
Gibbons E; Hoffmann M; Westhuyzen J; Hodgson A; Chick B; Last A
J Med Radiat Sci; 2023 Apr; 70 Suppl 2(Suppl 2):15-25. PubMed ID: 36148621
[TBL] [Abstract][Full Text] [Related]
17. Deep learning vs. atlas-based models for fast auto-segmentation of the masticatory muscles on head and neck CT images.
Chen W; Li Y; Dyer BA; Feng X; Rao S; Benedict SH; Chen Q; Rong Y
Radiat Oncol; 2020 Jul; 15(1):176. PubMed ID: 32690103
[TBL] [Abstract][Full Text] [Related]
18. Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers.
Wong J; Huang V; Wells D; Giambattista J; Giambattista J; Kolbeck C; Otto K; Saibishkumar EP; Alexander A
Radiat Oncol; 2021 Jun; 16(1):101. PubMed ID: 34103062
[TBL] [Abstract][Full Text] [Related]
19. Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.
Ahn SH; Yeo AU; Kim KH; Kim C; Goh Y; Cho S; Lee SB; Lim YK; Kim H; Shin D; Kim T; Kim TH; Youn SH; Oh ES; Jeong JH
Radiat Oncol; 2019 Nov; 14(1):213. PubMed ID: 31775825
[TBL] [Abstract][Full Text] [Related]
20. Deep learning based automatic segmentation of organs-at-risk for 0.35 T MRgRT of lung tumors.
Ribeiro MF; Marschner S; Kawula M; Rabe M; Corradini S; Belka C; Riboldi M; Landry G; Kurz C
Radiat Oncol; 2023 Aug; 18(1):135. PubMed ID: 37574549
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
