381 related articles for article (PubMed ID: 26328953)
1. Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer.
Hoang Duc AK; Eminowicz G; Mendes R; Wong SL; McClelland J; Modat M; Cardoso MJ; Mendelson AF; Veiga C; Kadir T; D'Souza D; Ourselin S
Med Phys; 2015 Sep; 42(9):5027-34. PubMed ID: 26328953
[TBL] [Abstract][Full Text] [Related]
2. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
3. Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk.
Thomson D; Boylan C; Liptrot T; Aitkenhead A; Lee L; Yap B; Sykes A; Rowbottom C; Slevin N
Radiat Oncol; 2014 Aug; 9():173. PubMed ID: 25086641
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis.
Liu P; Sun Y; Zhao X; Yan Y
Biomed Eng Online; 2023 Nov; 22(1):104. PubMed ID: 37915046
[TBL] [Abstract][Full Text] [Related]
7. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
Ibragimov B; Xing L
Med Phys; 2017 Feb; 44(2):547-557. PubMed ID: 28205307
[TBL] [Abstract][Full Text] [Related]
8. Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.
Sjöberg C; Lundmark M; Granberg C; Johansson S; Ahnesjö A; Montelius A
Radiat Oncol; 2013 Oct; 8():229. PubMed ID: 24090107
[TBL] [Abstract][Full Text] [Related]
9. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
Tong N; Gou S; Yang S; Cao M; Sheng K
Med Phys; 2019 Jun; 46(6):2669-2682. PubMed ID: 31002188
[TBL] [Abstract][Full Text] [Related]
10. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
[TBL] [Abstract][Full Text] [Related]
11. Clinical validation of atlas-based auto-segmentation of multiple target volumes and normal tissue (swallowing/mastication) structures in the head and neck.
Teguh DN; Levendag PC; Voet PW; Al-Mamgani A; Han X; Wolf TK; Hibbard LS; Nowak P; Akhiat H; Dirkx ML; Heijmen BJ; Hoogeman MS
Int J Radiat Oncol Biol Phys; 2011 Nov; 81(4):950-7. PubMed ID: 20932664
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.
D'Aviero A; Re A; Catucci F; Piccari D; Votta C; Piro D; Piras A; Di Dio C; Iezzi M; Preziosi F; Menna S; Quaranta F; Boschetti A; Marras M; Miccichè F; Gallus R; Indovina L; Bussu F; Valentini V; Cusumano D; Mattiucci GC
Int J Environ Res Public Health; 2022 Jul; 19(15):. PubMed ID: 35897425
[TBL] [Abstract][Full Text] [Related]
14. Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.
van Dijk LV; Van den Bosch L; Aljabar P; Peressutti D; Both S; J H M Steenbakkers R; Langendijk JA; Gooding MJ; Brouwer CL
Radiother Oncol; 2020 Jan; 142():115-123. PubMed ID: 31653573
[TBL] [Abstract][Full Text] [Related]
15. Head and neck multi-organ auto-segmentation on CT images aided by synthetic MRI.
Liu Y; Lei Y; Fu Y; Wang T; Zhou J; Jiang X; McDonald M; Beitler JJ; Curran WJ; Liu T; Yang X
Med Phys; 2020 Sep; 47(9):4294-4302. PubMed ID: 32648602
[TBL] [Abstract][Full Text] [Related]
16. Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images.
Zhang Z; Zhao T; Gay H; Zhang W; Sun B
Med Phys; 2021 Nov; 48(11):7052-7062. PubMed ID: 34655077
[TBL] [Abstract][Full Text] [Related]
17. The feasibility of atlas-based automatic segmentation of MRI for H&N radiotherapy planning.
Wardman K; Prestwich RJ; Gooding MJ; Speight RJ
J Appl Clin Med Phys; 2016 Jul; 17(4):146-154. PubMed ID: 27455480
[TBL] [Abstract][Full Text] [Related]
18. Automatic segmentation for adaptive planning in nasopharyngeal carcinoma IMRT: Time, geometrical, and dosimetric analysis.
Fung NTC; Hung WM; Sze CK; Lee MCH; Ng WT
Med Dosim; 2020 Spring; 45(1):60-65. PubMed ID: 31345672
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.
Oktay O; Nanavati J; Schwaighofer A; Carter D; Bristow M; Tanno R; Jena R; Barnett G; Noble D; Rimmer Y; Glocker B; O'Hara K; Bishop C; Alvarez-Valle J; Nori A
JAMA Netw Open; 2020 Nov; 3(11):e2027426. PubMed ID: 33252691
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of automatic atlas-based lymph node segmentation for head-and-neck cancer.
Stapleford LJ; Lawson JD; Perkins C; Edelman S; Davis L; McDonald MW; Waller A; Schreibmann E; Fox T
Int J Radiat Oncol Biol Phys; 2010 Jul; 77(3):959-66. PubMed ID: 20231069
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]