360 related articles for article (PubMed ID: 32282792)
21. ESC-Track: A computer workflow for 4-D segmentation, tracking, lineage tracing and dynamic context analysis of ESCs.
Fernández-de-Manúel L; Díaz-Díaz C; Jiménez-Carretero D; Torres M; Montoya MC
Biotechniques; 2017 May; 62(5):215-222. PubMed ID: 28528574
[TBL] [Abstract][Full Text] [Related]
22. Cheetah: A Computational Toolkit for Cybergenetic Control.
Pedone E; de Cesare I; Zamora-Chimal CG; Haener D; Postiglione L; La Regina A; Shannon B; Savery NJ; Grierson CS; di Bernardo M; Gorochowski TE; Marucci L
ACS Synth Biol; 2021 May; 10(5):979-989. PubMed ID: 33904719
[TBL] [Abstract][Full Text] [Related]
23. Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.
Chiang M; Hallman S; Cinquin A; de Mochel NR; Paz A; Kawauchi S; Calof AL; Cho KW; Fowlkes CC; Cinquin O
BMC Bioinformatics; 2015 Nov; 16():397. PubMed ID: 26607933
[TBL] [Abstract][Full Text] [Related]
24. A survey on applications of deep learning in microscopy image analysis.
Liu Z; Jin L; Chen J; Fang Q; Ablameyko S; Yin Z; Xu Y
Comput Biol Med; 2021 Jul; 134():104523. PubMed ID: 34091383
[TBL] [Abstract][Full Text] [Related]
25. Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.
Jelli E; Ohmura T; Netter N; Abt M; Jiménez-Siebert E; Neuhaus K; Rode DKH; Nadell CD; Drescher K
Mol Microbiol; 2023 Jun; 119(6):659-676. PubMed ID: 37066636
[TBL] [Abstract][Full Text] [Related]
26. LIM Tracker: a software package for cell tracking and analysis with advanced interactivity.
Aragaki H; Ogoh K; Kondo Y; Aoki K
Sci Rep; 2022 Feb; 12(1):2702. PubMed ID: 35177675
[TBL] [Abstract][Full Text] [Related]
27. Tracking cell lineages in 3D by incremental deep learning.
Sugawara K; Çevrim Ç; Averof M
Elife; 2022 Jan; 11():. PubMed ID: 34989675
[TBL] [Abstract][Full Text] [Related]
28. From pixels to insights: Machine learning and deep learning for bioimage analysis.
Jan M; Spangaro A; Lenartowicz M; Mattiazzi Usaj M
Bioessays; 2024 Feb; 46(2):e2300114. PubMed ID: 38058114
[TBL] [Abstract][Full Text] [Related]
29. BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies.
Mekterović I; Mekterović D; Maglica Z
BMC Bioinformatics; 2014 Jul; 15(1):251. PubMed ID: 25059528
[TBL] [Abstract][Full Text] [Related]
30. Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm.
Chou TC; You L; Beerens C; Feller KJ; Storteboom J; Chien MP
Cell Rep Methods; 2023 Nov; 3(11):100636. PubMed ID: 37963463
[TBL] [Abstract][Full Text] [Related]
31. CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.
Bray MA; Carpenter AE
BMC Bioinformatics; 2015 Nov; 16():368. PubMed ID: 26537300
[TBL] [Abstract][Full Text] [Related]
32. Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images.
Caicedo JC; Roth J; Goodman A; Becker T; Karhohs KW; Broisin M; Molnar C; McQuin C; Singh S; Theis FJ; Carpenter AE
Cytometry A; 2019 Sep; 95(9):952-965. PubMed ID: 31313519
[TBL] [Abstract][Full Text] [Related]
33. MIA is an open-source standalone deep learning application for microscopic image analysis.
Körber N
Cell Rep Methods; 2023 Jul; 3(7):100517. PubMed ID: 37533647
[TBL] [Abstract][Full Text] [Related]
34. Morphologically constrained and data informed cell segmentation of budding yeast.
Bakker E; Swain PS; Crane MM
Bioinformatics; 2018 Jan; 34(1):88-96. PubMed ID: 28968663
[TBL] [Abstract][Full Text] [Related]
35. Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software.
Kaiser M; Jug F; Julou T; Deshpande S; Pfohl T; Silander OK; Myers G; van Nimwegen E
Nat Commun; 2018 Jan; 9(1):212. PubMed ID: 29335514
[TBL] [Abstract][Full Text] [Related]
36. TrackMate: An open and extensible platform for single-particle tracking.
Tinevez JY; Perry N; Schindelin J; Hoopes GM; Reynolds GD; Laplantine E; Bednarek SY; Shorte SL; Eliceiri KW
Methods; 2017 Feb; 115():80-90. PubMed ID: 27713081
[TBL] [Abstract][Full Text] [Related]
37. Finding and following: a deep learning-based pipeline for tracking platelets during thrombus formation
McGovern AS; Larsson P; Tarlac V; Setiabakti N; Shabani Mashcool L; Hamilton JR; Boknäs N; Nunez-Iglesias J
Platelets; 2024 Dec; 35(1):2344512. PubMed ID: 38722090
[TBL] [Abstract][Full Text] [Related]
38. User-friendly tools for quantifying the dynamics of cellular morphology and intracellular protein clusters.
Tsygankov D; Chu PH; Chen H; Elston TC; Hahn KM
Methods Cell Biol; 2014; 123():409-27. PubMed ID: 24974040
[TBL] [Abstract][Full Text] [Related]
39. STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images.
Todorov H; Miguel Trabajo T; van der Meer JR
mSphere; 2023 Apr; 8(2):e0065822. PubMed ID: 36939355
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]