These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
174 related articles for article (PubMed ID: 39127060)
1. Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation. Huynh BN; Groendahl AR; Tomic O; Liland KH; Knudtsen IS; Hoebers F; van Elmpt W; Dale E; Malinen E; Futsaether CM Biomed Phys Eng Express; 2024 Aug; 10(5):. PubMed ID: 39127060 [No Abstract] [Full Text] [Related]
2. A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers. Groendahl AR; Skjei Knudtsen I; Huynh BN; Mulstad M; Moe YM; Knuth F; Tomic O; Indahl UG; Torheim T; Dale E; Malinen E; Futsaether CM Phys Med Biol; 2021 Mar; 66(6):065012. PubMed ID: 33666176 [TBL] [Abstract][Full Text] [Related]
3. Gross tumor volume segmentation for head and neck cancer radiotherapy using deep dense multi-modality network. Guo Z; Guo N; Gong K; Zhong S; Li Q Phys Med Biol; 2019 Oct; 64(20):205015. PubMed ID: 31514173 [TBL] [Abstract][Full Text] [Related]
4. Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers. Zhao Y; Wang X; Phan J; Chen X; Lee A; Yu C; Huang K; Court LE; Pan T; Wang H; Wahid KA; Mohamed ASR; Naser M; Fuller CD; Yang J Med Phys; 2024 Oct; 51(10):7295-7307. PubMed ID: 38896829 [TBL] [Abstract][Full Text] [Related]
5. Training deep-learning segmentation models from severely limited data. Zhao Y; Rhee DJ; Cardenas C; Court LE; Yang J Med Phys; 2021 Apr; 48(4):1697-1706. PubMed ID: 33474727 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging. Korte JC; Hardcastle N; Ng SP; Clark B; Kron T; Jackson P Med Phys; 2021 Dec; 48(12):7757-7772. PubMed ID: 34676555 [TBL] [Abstract][Full Text] [Related]
8. Automatic contouring of normal tissues with deep learning for preclinical radiation studies. Lappas G; Wolfs CJA; Staut N; Lieuwes NG; Biemans R; van Hoof SJ; Dubois LJ; Verhaegen F Phys Med Biol; 2022 Feb; 67(4):. PubMed ID: 35061600 [No Abstract] [Full Text] [Related]
9. Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI. Groendahl AR; Moe YM; Kaushal CK; Huynh BN; Rusten E; Tomic O; Hernes E; Hanekamp B; Undseth C; Guren MG; Malinen E; Futsaether CM Acta Oncol; 2022 Jan; 61(1):89-96. PubMed ID: 34783610 [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. Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning. Groendahl AR; Huynh BN; Tomic O; Søvik Å; Dale E; Malinen E; Skogmo HK; Futsaether CM Front Vet Sci; 2023; 10():1143986. PubMed ID: 37026102 [TBL] [Abstract][Full Text] [Related]
12. Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients. Moe YM; Groendahl AR; Tomic O; Dale E; Malinen E; Futsaether CM Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2782-2792. PubMed ID: 33559711 [TBL] [Abstract][Full Text] [Related]
13. Evaluating Automatic Segmentation for Swallowing-Related Organs for Head and Neck Cancer. Li Y; Rao S; Chen W; Azghadi SF; Nguyen KNB; Moran A; Usera BM; Dyer BA; Shang L; Chen Q; Rong Y Technol Cancer Res Treat; 2022; 21():15330338221105724. PubMed ID: 35790457 [No Abstract] [Full Text] [Related]
14. Information fusion for fully automated segmentation of head and neck tumors from PET and CT images. Shiri I; Amini M; Yousefirizi F; Vafaei Sadr A; Hajianfar G; Salimi Y; Mansouri Z; Jenabi E; Maghsudi M; Mainta I; Becker M; Rahmim A; Zaidi H Med Phys; 2024 Jan; 51(1):319-333. PubMed ID: 37475591 [TBL] [Abstract][Full Text] [Related]
15. Hippocampus segmentation in CT using deep learning: impact of MR versus CT-based training contours. Hänsch A; Hendrik Moltz J; Geisler B; Engel C; Klein J; Genghi A; Schreier J; Morgas T; Haas B J Med Imaging (Bellingham); 2020 Nov; 7(6):064001. PubMed ID: 33195733 [No Abstract] [Full Text] [Related]
16. 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]
17. Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms. Shiri I; Arabi H; Sanaat A; Jenabi E; Becker M; Zaidi H Clin Nucl Med; 2021 Nov; 46(11):872-883. PubMed ID: 34238799 [TBL] [Abstract][Full Text] [Related]
18. An uncertainty-aware deep learning architecture with outlier mitigation for prostate gland segmentation in radiotherapy treatment planning. Li X; Bagher-Ebadian H; Gardner S; Kim J; Elshaikh M; Movsas B; Zhu D; Chetty IJ Med Phys; 2023 Jan; 50(1):311-322. PubMed ID: 36112996 [TBL] [Abstract][Full Text] [Related]
19. A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning. Chan JW; Kearney V; Haaf S; Wu S; Bogdanov M; Reddick M; Dixit N; Sudhyadhom A; Chen J; Yom SS; Solberg TD Med Phys; 2019 May; 46(5):2204-2213. PubMed ID: 30887523 [TBL] [Abstract][Full Text] [Related]
20. Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout. Zhao LM; Zhang H; Kim DD; Ghimire K; Hu R; Kargilis DC; Tang L; Meng S; Chen Q; Liao WH; Bai H; Jiao Z; Feng X Phys Med Biol; 2023 Apr; 68(9):. PubMed ID: 37019119 [No Abstract] [Full Text] [Related] [Next] [New Search]