165 related articles for article (PubMed ID: 37426758)
1. DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.
Zargari A; Lodewijk GA; Mashhadi N; Cook N; Neudorf CW; Araghbidikashani K; Hays R; Kozuki S; Rubio S; Hrabeta-Robinson E; Brooks A; Hinck L; Shariati SA
Cell Rep Methods; 2023 Jun; 3(6):100500. PubMed ID: 37426758
[TBL] [Abstract][Full Text] [Related]
2. 3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.
Wen C; Miura T; Voleti V; Yamaguchi K; Tsutsumi M; Yamamoto K; Otomo K; Fujie Y; Teramoto T; Ishihara T; Aoki K; Nemoto T; Hillman EM; Kimura KD
Elife; 2021 Mar; 10():. PubMed ID: 33781383
[TBL] [Abstract][Full Text] [Related]
3. A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.
Liu AA; Li K; Kanade T
IEEE Trans Med Imaging; 2012 Feb; 31(2):359-69. PubMed ID: 21954199
[TBL] [Abstract][Full Text] [Related]
4. DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics.
O'Connor OM; Alnahhas RN; Lugagne JB; Dunlop MJ
PLoS Comput Biol; 2022 Jan; 18(1):e1009797. PubMed ID: 35041653
[TBL] [Abstract][Full Text] [Related]
5. CAST: An automated segmentation and tracking tool for the analysis of transcriptional kinetics from single-cell time-lapse recordings.
Blanchoud S; Nicolas D; Zoller B; Tidin O; Naef F
Methods; 2015 Sep; 85():3-11. PubMed ID: 25934263
[TBL] [Abstract][Full Text] [Related]
6. Automatic improvement of deep learning-based cell segmentation in time-lapse microscopy by neural architecture search.
Zhu Y; Meijering E
Bioinformatics; 2021 Dec; 37(24):4844-4850. PubMed ID: 34329376
[TBL] [Abstract][Full Text] [Related]
7. Automatic detection and analysis of cell motility in phase-contrast time-lapse images using a combination of maximally stable extremal regions and Kalman filter approaches.
Kaakinen M; Huttunen S; Paavolainen L; Marjomäki V; Heikkilä J; Eklund L
J Microsc; 2014 Jan; 253(1):65-78. PubMed ID: 24279418
[TBL] [Abstract][Full Text] [Related]
8. Vertebrate neural stem cell segmentation, tracking and lineaging with validation and editing.
Winter M; Wait E; Roysam B; Goderie SK; Ali RA; Kokovay E; Temple S; Cohen AR
Nat Protoc; 2011 Nov; 6(12):1942-52. PubMed ID: 22094730
[TBL] [Abstract][Full Text] [Related]
9. Segmentation Method of Time-Lapse Microscopy Images with the Focus on Biocompatibility Assessment.
Soukup J; Císař P; Šroubek F
Microsc Microanal; 2016 Jun; 22(3):497-506. PubMed ID: 27132464
[TBL] [Abstract][Full Text] [Related]
10. Automatic three-dimensional segmentation of mouse embryonic stem cell nuclei by utilising multiple channels of confocal fluorescence images.
Chang YH; Yokota H; Abe K; Tasi MD; Chu SL
J Microsc; 2021 Jan; 281(1):57-75. PubMed ID: 32720710
[TBL] [Abstract][Full Text] [Related]
11. Segmenting time-lapse phase contrast images of adjacent NIH 3T3 cells.
Chalfoun J; Kociolek M; Dima A; Halter M; Cardone A; Peskin A; Bajcsy P; Brady M
J Microsc; 2013 Jan; 249(1):41-52. PubMed ID: 23126432
[TBL] [Abstract][Full Text] [Related]
12. Tracking biological cells in time-lapse microscopy: an adaptive technique combining motion and topological features.
Dewan MA; Ahmad MO; Swamy MN
IEEE Trans Biomed Eng; 2011 Jun; 58(6):1637-47. PubMed ID: 21278009
[TBL] [Abstract][Full Text] [Related]
13. A deep learning-based segmentation pipeline for profiling cellular morphodynamics using multiple types of live cell microscopy.
Jang J; Wang C; Zhang X; Choi HJ; Pan X; Lin B; Yu Y; Whittle C; Ryan M; Chen Y; Lee K
Cell Rep Methods; 2021 Nov; 1(7):. PubMed ID: 34888542
[TBL] [Abstract][Full Text] [Related]
14. Segmentation, Detection, and Tracking of Stem Cell Image by Digital Twins and Lightweight Deep Learning.
Du X; Liu M; Sun Y
Comput Intell Neurosci; 2022; 2022():6003293. PubMed ID: 35422850
[TBL] [Abstract][Full Text] [Related]
15. DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.
Lugagne JB; Lin H; Dunlop MJ
PLoS Comput Biol; 2020 Apr; 16(4):e1007673. PubMed ID: 32282792
[TBL] [Abstract][Full Text] [Related]
16. Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.
Brandes S; Mokhtari Z; Essig F; Hünniger K; Kurzai O; Figge MT
Med Image Anal; 2015 Feb; 20(1):34-51. PubMed ID: 25465844
[TBL] [Abstract][Full Text] [Related]
17. Automated segmentation and tracking of mitochondria in live-cell time-lapse images.
Lefebvre AEYT; Ma D; Kessenbrock K; Lawson DA; Digman MA
Nat Methods; 2021 Sep; 18(9):1091-1102. PubMed ID: 34413523
[TBL] [Abstract][Full Text] [Related]
18. Sequential Saliency Guided Deep Neural Network for Joint Mitosis Identification and Localization in Time-Lapse Phase Contrast Microscopy Images.
Lu Y; Liu AA; Chen M; Nie WZ; Su YT
IEEE J Biomed Health Inform; 2020 May; 24(5):1367-1378. PubMed ID: 31545751
[TBL] [Abstract][Full Text] [Related]
19. Automated profiling of individual cell-cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING).
Merouane A; Rey-Villamizar N; Lu Y; Liadi I; Romain G; Lu J; Singh H; Cooper LJ; Varadarajan N; Roysam B
Bioinformatics; 2015 Oct; 31(19):3189-97. PubMed ID: 26059718
[TBL] [Abstract][Full Text] [Related]
20. A novel framework for cellular tracking and mitosis detection in dense phase contrast microscopy images.
Thirusittampalam K; Hossain MJ; Ghita O; Whelan PF
IEEE J Biomed Health Inform; 2013 May; 17(3):642-53. PubMed ID: 24592465
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
