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.
3. Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline. Wang J; Vachet C; Rumple A; Gouttard S; Ouziel C; Perrot E; Du G; Huang X; Gerig G; Styner M Front Neuroinform; 2014; 8():7. PubMed ID: 24567717 [TBL] [Abstract][Full Text] [Related]
4. A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction. Ballanger B; Tremblay L; Sgambato-Faure V; Beaudoin-Gobert M; Lavenne F; Le Bars D; Costes N Neuroimage; 2013 Aug; 77():26-43. PubMed ID: 23537938 [TBL] [Abstract][Full Text] [Related]
5. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates. Pipitone J; Park MT; Winterburn J; Lett TA; Lerch JP; Pruessner JC; Lepage M; Voineskos AN; Chakravarty MM; Neuroimage; 2014 Nov; 101():494-512. PubMed ID: 24784800 [TBL] [Abstract][Full Text] [Related]
6. Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors. Clèrigues A; Valverde S; Oliver A; Lladó X; Comput Biol Med; 2024 Sep; 179():108811. PubMed ID: 38991315 [TBL] [Abstract][Full Text] [Related]
7. Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility. Li X; Chen L; Kutten K; Ceritoglu C; Li Y; Kang N; Hsu JT; Qiao Y; Wei H; Liu C; Miller MI; Mori S; Yousem DM; van Zijl PCM; Faria AV Neuroimage; 2019 May; 191():337-349. PubMed ID: 30738207 [TBL] [Abstract][Full Text] [Related]
8. Automated joint skull-stripping and segmentation with Multi-Task U-Net in large mouse brain MRI databases. De Feo R; Shatillo A; Sierra A; Valverde JM; Gröhn O; Giove F; Tohka J Neuroimage; 2021 Apr; 229():117734. PubMed ID: 33454412 [TBL] [Abstract][Full Text] [Related]
9. Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles. Tang X; Crocetti D; Kutten K; Ceritoglu C; Albert MS; Mori S; Mostofsky SH; Miller MI Front Neurosci; 2015; 9():61. PubMed ID: 25784852 [TBL] [Abstract][Full Text] [Related]
10. A Deep Learning Framework for Skull Stripping in Brain MRI. Tabassum M; Al Suman A; Russo C; Di Ieva A; Liu S Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38082786 [TBL] [Abstract][Full Text] [Related]
11. Automated olfactory bulb segmentation on high resolutional T2-weighted MRI. Estrada S; Lu R; Diers K; Zeng W; Ehses P; Stöcker T; Breteler MMB; Reuter M Neuroimage; 2021 Nov; 242():118464. PubMed ID: 34389442 [TBL] [Abstract][Full Text] [Related]
12. Automatic macaque brain segmentation based on 7T MRI. Zhao J; Chen W; Liu C; Gao Y; Chen X; Chen G; Xia L; Dai Y; Zhang X Magn Reson Imaging; 2022 Oct; 92():232-242. PubMed ID: 35842194 [TBL] [Abstract][Full Text] [Related]
13. Generalizing deep learning brain segmentation for skull removal and intracranial measurements. Liu Y; Huo Y; Dewey B; Wei Y; Lyu I; Landman BA Magn Reson Imaging; 2022 May; 88():44-52. PubMed ID: 34999162 [TBL] [Abstract][Full Text] [Related]
14. A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging. Bagci U; Foster B; Miller-Jaster K; Luna B; Dey B; Bishai WR; Jonsson CB; Jain S; Mollura DJ EJNMMI Res; 2013 Jul; 3(1):55. PubMed ID: 23879987 [TBL] [Abstract][Full Text] [Related]
15. Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri). Pallast N; Diedenhofen M; Blaschke S; Wieters F; Wiedermann D; Hoehn M; Fink GR; Aswendt M Front Neuroinform; 2019; 13():42. PubMed ID: 31231202 [TBL] [Abstract][Full Text] [Related]
16. An automatic and accurate deep learning-based neuroimaging pipeline for the neonatal brain. Shen DD; Bao SL; Wang Y; Chen YC; Zhang YC; Li XC; Ding YC; Jia ZZ Pediatr Radiol; 2023 Jul; 53(8):1685-1697. PubMed ID: 36884052 [TBL] [Abstract][Full Text] [Related]
17. RU-Net: skull stripping in rat brain MR images after ischemic stroke with rat U-Net. Chang HH; Yeh SJ; Chiang MC; Hsieh ST BMC Med Imaging; 2023 Mar; 23(1):44. PubMed ID: 36973775 [TBL] [Abstract][Full Text] [Related]
18. 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]
19. Automatic Skull Stripping of Rat and Mouse Brain MRI Data Using U-Net. Hsu LM; Wang S; Ranadive P; Ban W; Chao TH; Song S; Cerri DH; Walton LR; Broadwater MA; Lee SH; Shen D; Shih YI Front Neurosci; 2020; 14():568614. PubMed ID: 33117118 [TBL] [Abstract][Full Text] [Related]
20. Using deep learning to segment breast and fibroglandular tissue in MRI volumes. Dalmış MU; Litjens G; Holland K; Setio A; Mann R; Karssemeijer N; Gubern-Mérida A Med Phys; 2017 Feb; 44(2):533-546. PubMed ID: 28035663 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]