209 related articles for article (PubMed ID: 36900410)
1. Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images.
Veiga-Canuto D; Cerdà-Alberich L; Jiménez-Pastor A; Carot Sierra JM; Gomis-Maya A; Sangüesa-Nebot C; Fernández-Patón M; Martínez de Las Heras B; Taschner-Mandl S; Düster V; Pötschger U; Simon T; Neri E; Alberich-Bayarri Á; Cañete A; Hero B; Ladenstein R; Martí-Bonmatí L
Cancers (Basel); 2023 Mar; 15(5):. PubMed ID: 36900410
[TBL] [Abstract][Full Text] [Related]
2. Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images.
Veiga-Canuto D; Cerdà-Alberich L; Sangüesa Nebot C; Martínez de Las Heras B; Pötschger U; Gabelloni M; Carot Sierra JM; Taschner-Mandl S; Düster V; Cañete A; Ladenstein R; Neri E; Martí-Bonmatí L
Cancers (Basel); 2022 Jul; 14(15):. PubMed ID: 35954314
[TBL] [Abstract][Full Text] [Related]
3. Segmentation of whole breast and fibroglandular tissue using nnU-Net in dynamic contrast enhanced MR images.
Huo L; Hu X; Xiao Q; Gu Y; Chu X; Jiang L
Magn Reson Imaging; 2021 Oct; 82():31-41. PubMed ID: 34147598
[TBL] [Abstract][Full Text] [Related]
4. Automatic liver segmentation and assessment of liver fibrosis using deep learning with MR T1-weighted images in rats.
Zhang W; Zhao N; Gao Y; Huang B; Wang L; Zhou X; Li Z
Magn Reson Imaging; 2024 Apr; 107():1-7. PubMed ID: 38147969
[TBL] [Abstract][Full Text] [Related]
5. Deep learning-based multimodal segmentation of oropharyngeal squamous cell carcinoma on CT and MRI using self-configuring nnU-Net.
Choi Y; Bang J; Kim SY; Seo M; Jang J
Eur Radiol; 2024 Jan; ():. PubMed ID: 38243135
[TBL] [Abstract][Full Text] [Related]
6. Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net.
Zhu HT; Zhang XY; Shi YJ; Li XT; Sun YS
J Appl Clin Med Phys; 2021 Sep; 22(9):324-331. PubMed ID: 34343402
[TBL] [Abstract][Full Text] [Related]
7. Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.
Orlando N; Gillies DJ; Gyacskov I; Romagnoli C; D'Souza D; Fenster A
Med Phys; 2020 Jun; 47(6):2413-2426. PubMed ID: 32166768
[TBL] [Abstract][Full Text] [Related]
8. Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study.
Wennmann M; Neher P; Stanczyk N; Kahl KC; Kächele J; Weru V; Hielscher T; Grözinger M; Chmelik J; Zhang KS; Bauer F; Nonnenmacher T; Debic M; Sauer S; Rotkopf LT; Jauch A; Schlamp K; Mai EK; Weinhold N; Afat S; Horger M; Goldschmidt H; Schlemmer HP; Weber TF; Delorme S; Kurz FT; Maier-Hein K
Invest Radiol; 2023 Apr; 58(4):273-282. PubMed ID: 36256790
[TBL] [Abstract][Full Text] [Related]
9. Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.
Vossough A; Khalili N; Familiar AM; Gandhi D; Viswanathan K; Tu W; Haldar D; Bagheri S; Anderson H; Haldar S; Storm PB; Resnick A; Ware JB; Nabavizadeh A; Fathi Kazerooni A
AJNR Am J Neuroradiol; 2024 May; ():. PubMed ID: 38724204
[TBL] [Abstract][Full Text] [Related]
10. A Fully Automated Deep-Learning Model for Predicting the Molecular Subtypes of Posterior Fossa Ependymomas Using T2-Weighted Images.
Cheng D; Zhuo Z; Du J; Weng J; Zhang C; Duan Y; Sun T; Wu M; Guo M; Hua T; Jin Y; Peng B; Li Z; Zhu M; Imami M; Bettegowda C; Sair H; Bai HX; Barkhof F; Liu X; Liu Y
Clin Cancer Res; 2024 Jan; 30(1):150-158. PubMed ID: 37916978
[TBL] [Abstract][Full Text] [Related]
11. Does Anatomical Contextual Information Improve 3D U-Net-Based Brain Tumor Segmentation?
Tampu IE; Haj-Hosseini N; Eklund A
Diagnostics (Basel); 2021 Jun; 11(7):. PubMed ID: 34201964
[TBL] [Abstract][Full Text] [Related]
12. CNN-based fully automatic wrist cartilage volume quantification in MR images: A comparative analysis between different CNN architectures.
Vladimirov N; Brui E; Levchuk A; Al-Haidri W; Fokin V; Efimtcev A; Bendahan D
Magn Reson Med; 2023 Aug; 90(2):737-751. PubMed ID: 37094028
[TBL] [Abstract][Full Text] [Related]
13. Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.
Zhang L; Mohamed AA; Chai R; Guo Y; Zheng B; Wu S
J Magn Reson Imaging; 2020 Feb; 51(2):635-643. PubMed ID: 31301201
[TBL] [Abstract][Full Text] [Related]
14. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
15. Automatic segmentation of organs at risk and tumors in CT images of lung cancer from partially labelled datasets with a semi-supervised conditional nnU-Net.
Zhang G; Yang Z; Huo B; Chai S; Jiang S
Comput Methods Programs Biomed; 2021 Nov; 211():106419. PubMed ID: 34563895
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
[TBL] [Abstract][Full Text] [Related]
17. Fully automated bladder tumor segmentation from T2 MRI images using 3D U-Net algorithm.
Coroamă DM; Dioșan L; Telecan T; Andras I; Crișan N; Medan P; Andreica A; Caraiani C; Lebovici A; Boca B; Bálint Z
Front Oncol; 2023; 13():1096136. PubMed ID: 36969047
[TBL] [Abstract][Full Text] [Related]
18. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation.
Choi Y; Nam Y; Lee YS; Kim J; Ahn KJ; Jang J; Shin NY; Kim BS; Jeon SS
Eur J Radiol; 2020 Jul; 128():109031. PubMed ID: 32417712
[TBL] [Abstract][Full Text] [Related]
19. Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.
Abbani N; Baudier T; Rit S; Franco FD; Okoli F; Jaouen V; Tilquin F; Barateau A; Simon A; de Crevoisier R; Bert J; Sarrut D
Med Phys; 2022 Nov; 49(11):6930-6944. PubMed ID: 36000762
[TBL] [Abstract][Full Text] [Related]
20. NnU-Net versus mesh growing algorithm as a tool for the robust and timely segmentation of neurosurgical 3D images in contrast-enhanced T1 MRI scans.
de Boer M; Kos TM; Fick T; van Doormaal JAM; Colombo E; Kuijf HJ; Robe PAJT; Regli LP; Bartels LW; van Doormaal TPC
Acta Neurochir (Wien); 2024 Feb; 166(1):92. PubMed ID: 38376564
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
