225 related articles for article (PubMed ID: 32603860)
1. Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.
Thakur S; Doshi J; Pati S; Rathore S; Sako C; Bilello M; Ha SM; Shukla G; Flanders A; Kotrotsou A; Milchenko M; Liem S; Alexander GS; Lombardo J; Palmer JD; LaMontagne P; Nazeri A; Talbar S; Kulkarni U; Marcus D; Colen R; Davatzikos C; Erus G; Bakas S
Neuroimage; 2020 Oct; 220():117081. PubMed ID: 32603860
[TBL] [Abstract][Full Text] [Related]
2. Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning.
Thakur SP; Doshi J; Pati S; Ha SM; Sako C; Talbar S; Kulkarni U; Davatzikos C; Erus G; Bakas S
Brainlesion; 2019 Oct; 11992():57-68. PubMed ID: 32577629
[TBL] [Abstract][Full Text] [Related]
3. Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.
Osman AFI; Al-Mugren KS; Tamam NM; Shahine B
Radiat Oncol; 2024 May; 19(1):61. PubMed ID: 38773620
[TBL] [Abstract][Full Text] [Related]
4. A general skull stripping of multiparametric brain MRIs using 3D convolutional neural network.
Pei L; Ak M; Tahon NHM; Zenkin S; Alkarawi S; Kamal A; Yilmaz M; Chen L; Er M; Ak N; Colen R
Sci Rep; 2022 Jun; 12(1):10826. PubMed ID: 35760886
[TBL] [Abstract][Full Text] [Related]
5. Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.
Perkuhn M; Stavrinou P; Thiele F; Shakirin G; Mohan M; Garmpis D; Kabbasch C; Borggrefe J
Invest Radiol; 2018 Nov; 53(11):647-654. PubMed ID: 29863600
[TBL] [Abstract][Full Text] [Related]
6. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.
Sauwen N; Acou M; Van Cauter S; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Van Huffel S
Neuroimage Clin; 2016; 12():753-764. PubMed ID: 27812502
[TBL] [Abstract][Full Text] [Related]
7. Automated, fast, robust brain extraction on contrast-enhanced T1-weighted MRI in presence of brain tumors: an optimized model based on multi-center datasets.
Teng Y; Chen C; Shu X; Zhao F; Zhang L; Xu J
Eur Radiol; 2024 Feb; 34(2):1190-1199. PubMed ID: 37615767
[TBL] [Abstract][Full Text] [Related]
8. A generalizable brain extraction net (BEN) for multimodal MRI data from rodents, nonhuman primates, and humans.
Yu Z; Han X; Xu W; Zhang J; Marr C; Shen D; Peng T; Zhang XY; Feng J
Elife; 2022 Dec; 11():. PubMed ID: 36546674
[TBL] [Abstract][Full Text] [Related]
9. Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features.
Bakas S; Akbari H; Sotiras A; Bilello M; Rozycki M; Kirby JS; Freymann JB; Farahani K; Davatzikos C
Sci Data; 2017 Sep; 4():170117. PubMed ID: 28872634
[TBL] [Abstract][Full Text] [Related]
10. Robust skull stripping using multiple MR image contrasts insensitive to pathology.
Roy S; Butman JA; Pham DL;
Neuroimage; 2017 Feb; 146():132-147. PubMed ID: 27864083
[TBL] [Abstract][Full Text] [Related]
11. Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.
Pemberton HG; Wu J; Kommers I; Müller DMJ; Hu Y; Goodkin O; Vos SB; Bisdas S; Robe PA; Ardon H; Bello L; Rossi M; Sciortino T; Nibali MC; Berger MS; Hervey-Jumper SL; Bouwknegt W; Van den Brink WA; Furtner J; Han SJ; Idema AJS; Kiesel B; Widhalm G; Kloet A; Wagemakers M; Zwinderman AH; Krieg SM; Mandonnet E; Prados F; de Witt Hamer P; Barkhof F; Eijgelaar RS
Sci Rep; 2023 Nov; 13(1):18911. PubMed ID: 37919354
[TBL] [Abstract][Full Text] [Related]
12. An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD.
Yazdan SA; Ahmad R; Iqbal N; Rizwan A; Khan AN; Kim DH
Tomography; 2022 Jul; 8(4):1905-1927. PubMed ID: 35894026
[TBL] [Abstract][Full Text] [Related]
13. Deep semi-supervised learning for brain tumor classification.
Ge C; Gu IY; Jakola AS; Yang J
BMC Med Imaging; 2020 Jul; 20(1):87. PubMed ID: 32727476
[TBL] [Abstract][Full Text] [Related]
14. Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.
Kickingereder P; Isensee F; Tursunova I; Petersen J; Neuberger U; Bonekamp D; Brugnara G; Schell M; Kessler T; Foltyn M; Harting I; Sahm F; Prager M; Nowosielski M; Wick A; Nolden M; Radbruch A; Debus J; Schlemmer HP; Heiland S; Platten M; von Deimling A; van den Bent MJ; Gorlia T; Wick W; Bendszus M; Maier-Hein KH
Lancet Oncol; 2019 May; 20(5):728-740. PubMed ID: 30952559
[TBL] [Abstract][Full Text] [Related]
15. Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.
Dieckhaus H; Meijboom R; Okar S; Wu T; Parvathaneni P; Mina Y; Chandran S; Waldman AD; Reich DS; Nair G
Top Magn Reson Imaging; 2022 Jun; 31(3):31-39. PubMed ID: 35767314
[TBL] [Abstract][Full Text] [Related]
16. Automated glioma grading on conventional MRI images using deep convolutional neural networks.
Zhuge Y; Ning H; Mathen P; Cheng JY; Krauze AV; Camphausen K; Miller RW
Med Phys; 2020 Jul; 47(7):3044-3053. PubMed ID: 32277478
[TBL] [Abstract][Full Text] [Related]
17. Automated neonatal nnU-Net brain MRI extractor trained on a large multi-institutional dataset.
Chen JV; Li Y; Tang F; Chaudhari G; Lew C; Lee A; Rauschecker AM; Haskell-Mendoza AP; Wu YW; Calabrese E
Sci Rep; 2024 Feb; 14(1):4583. PubMed ID: 38403673
[TBL] [Abstract][Full Text] [Related]
18. SynthStrip: skull-stripping for any brain image.
Hoopes A; Mora JS; Dalca AV; Fischl B; Hoffmann M
Neuroimage; 2022 Oct; 260():119474. PubMed ID: 35842095
[TBL] [Abstract][Full Text] [Related]
19. Segmenting pediatric optic pathway gliomas from MRI using deep learning.
Nalepa J; Adamski S; Kotowski K; Chelstowska S; Machnikowska-Sokolowska M; Bozek O; Wisz A; Jurkiewicz E
Comput Biol Med; 2022 Mar; 142():105237. PubMed ID: 35074737
[TBL] [Abstract][Full Text] [Related]
20. Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study.
Badrigilan S; Nabavi S; Abin AA; Rostampour N; Abedi I; Shirvani A; Ebrahimi Moghaddam M
Int J Comput Assist Radiol Surg; 2021 Apr; 16(4):529-542. PubMed ID: 33666859
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]