348 related articles for article (PubMed ID: 34255661)
21. Automated delineation of head and neck organs at risk using synthetic MRI-aided mask scoring regional convolutional neural network.
Dai X; Lei Y; Wang T; Zhou J; Roper J; McDonald M; Beitler JJ; Curran WJ; Liu T; Yang X
Med Phys; 2021 Oct; 48(10):5862-5873. PubMed ID: 34342878
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Improved accuracy of auto-segmentation of organs at risk in radiotherapy planning for nasopharyngeal carcinoma based on fully convolutional neural network deep learning.
Peng Y; Liu Y; Shen G; Chen Z; Chen M; Miao J; Zhao C; Deng J; Qi Z; Deng X
Oral Oncol; 2023 Jan; 136():106261. PubMed ID: 36446186
[TBL] [Abstract][Full Text] [Related]
24. Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images.
Wang Y; Lombardo E; Huang L; Avanzo M; Fanetti G; Franchin G; Zschaeck S; Weingärtner J; Belka C; Riboldi M; Kurz C; Landry G
Radiat Oncol; 2024 Jan; 19(1):3. PubMed ID: 38191431
[TBL] [Abstract][Full Text] [Related]
25. Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.
Kihara S; Koike Y; Takegawa H; Anetai Y; Nakamura S; Tanigawa N; Koizumi M
Med Dosim; 2023 Spring; 48(1):20-24. PubMed ID: 36273950
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.
Chen X; Sun S; Bai N; Han K; Liu Q; Yao S; Tang H; Zhang C; Lu Z; Huang Q; Zhao G; Xu Y; Chen T; Xie X; Liu Y
Radiother Oncol; 2021 Jul; 160():175-184. PubMed ID: 33961914
[TBL] [Abstract][Full Text] [Related]
28. Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT.
Iyer A; Thor M; Onochie I; Hesse J; Zakeri K; LoCastro E; Jiang J; Veeraraghavan H; Elguindi S; Lee NY; Deasy JO; Apte AP
Phys Med Biol; 2022 Jan; 67(2):. PubMed ID: 34874302
[No Abstract] [Full Text] [Related]
29. An evaluation of MR based deep learning auto-contouring for planning head and neck radiotherapy.
Hague C; McPartlin A; Lee LW; Hughes C; Mullan D; Beasley W; Green A; Price G; Whitehurst P; Slevin N; van Herk M; West C; Chuter R
Radiother Oncol; 2021 May; 158():112-117. PubMed ID: 33636229
[TBL] [Abstract][Full Text] [Related]
30. A Preliminary Experience of Implementing Deep-Learning Based Auto-Segmentation in Head and Neck Cancer: A Study on Real-World Clinical Cases.
Zhong Y; Yang Y; Fang Y; Wang J; Hu W
Front Oncol; 2021; 11():638197. PubMed ID: 34026615
[TBL] [Abstract][Full Text] [Related]
31. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
[TBL] [Abstract][Full Text] [Related]
32. 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]
33. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
[TBL] [Abstract][Full Text] [Related]
34. Comparing different CT, PET and MRI multi-modality image combinations for deep learning-based head and neck tumor segmentation.
Ren J; Eriksen JG; Nijkamp J; Korreman SS
Acta Oncol; 2021 Nov; 60(11):1399-1406. PubMed ID: 34264157
[TBL] [Abstract][Full Text] [Related]
35. Comparative evaluation of a prototype deep learning algorithm for autosegmentation of normal tissues in head and neck radiotherapy.
Koo J; Caudell JJ; Latifi K; Jordan P; Shen S; Adamson PM; Moros EG; Feygelman V
Radiother Oncol; 2022 Sep; 174():52-58. PubMed ID: 35817322
[TBL] [Abstract][Full Text] [Related]
36. Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning.
Liang S; Tang F; Huang X; Yang K; Zhong T; Hu R; Liu S; Yuan X; Zhang Y
Eur Radiol; 2019 Apr; 29(4):1961-1967. PubMed ID: 30302589
[TBL] [Abstract][Full Text] [Related]
37. Deep learning for elective neck delineation: More consistent and time efficient.
van der Veen J; Willems S; Bollen H; Maes F; Nuyts S
Radiother Oncol; 2020 Dec; 153():180-188. PubMed ID: 33065182
[TBL] [Abstract][Full Text] [Related]
38. Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.
Men K; Dai J; Li Y
Med Phys; 2017 Dec; 44(12):6377-6389. PubMed ID: 28963779
[TBL] [Abstract][Full Text] [Related]
39. Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours.
Fritscher KD; Peroni M; Zaffino P; Spadea MF; Schubert R; Sharp G
Med Phys; 2014 May; 41(5):051910. PubMed ID: 24784389
[TBL] [Abstract][Full Text] [Related]
40. General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis.
Amjad A; Xu J; Thill D; Lawton C; Hall W; Awan MJ; Shukla M; Erickson BA; Li XA
Med Phys; 2022 Mar; 49(3):1686-1700. PubMed ID: 35094390
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]