365 related articles for article (PubMed ID: 32282792)
41. Tracking bacteria at high density with FAST, the Feature-Assisted Segmenter/Tracker.
Meacock OJ; Durham WM
PLoS Comput Biol; 2023 Oct; 19(10):e1011524. PubMed ID: 37812642
[TBL] [Abstract][Full Text] [Related]
42. Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis.
Paintdakhi A; Parry B; Campos M; Irnov I; Elf J; Surovtsev I; Jacobs-Wagner C
Mol Microbiol; 2016 Feb; 99(4):767-77. PubMed ID: 26538279
[TBL] [Abstract][Full Text] [Related]
43. Using CellX to quantify intracellular events.
Mayer C; Dimopoulos S; Rudolf F; Stelling J
Curr Protoc Mol Biol; 2013; Chapter 14():Unit 14.22.. PubMed ID: 23288460
[TBL] [Abstract][Full Text] [Related]
44. Automated cell boundary and 3D nuclear segmentation of cells in suspension.
Kesler B; Li G; Thiemicke A; Venkat R; Neuert G
Sci Rep; 2019 Jul; 9(1):10237. PubMed ID: 31308458
[TBL] [Abstract][Full Text] [Related]
45. MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.
Courtney J; Woods E; Scholz D; Hall WW; Gautier VW
PLoS One; 2015; 10(10):e0140209. PubMed ID: 26485569
[TBL] [Abstract][Full Text] [Related]
46. Methods for cell and particle tracking.
Meijering E; Dzyubachyk O; Smal I
Methods Enzymol; 2012; 504():183-200. PubMed ID: 22264535
[TBL] [Abstract][Full Text] [Related]
47. A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos.
Arbelle A; Reyes J; Chen JY; Lahav G; Riklin Raviv T
Med Image Anal; 2018 Jul; 47():140-152. PubMed ID: 29747154
[TBL] [Abstract][Full Text] [Related]
48. Automated Cell Tracking Using Motion Prediction-Based Matching and Event Handling.
Boukari F; Makrogiannis S
IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(3):959-971. PubMed ID: 30334766
[TBL] [Abstract][Full Text] [Related]
49. 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]
50. Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.
Wen C
Methods Mol Biol; 2024; 2800():203-215. PubMed ID: 38709486
[TBL] [Abstract][Full Text] [Related]
51. Image generation by GAN and style transfer for agar plate image segmentation.
Andreini P; Bonechi S; Bianchini M; Mecocci A; Scarselli F
Comput Methods Programs Biomed; 2020 Feb; 184():105268. PubMed ID: 31891902
[TBL] [Abstract][Full Text] [Related]
52. Using Cell-ID 1.4 with R for microscope-based cytometry.
Bush A; Chernomoretz A; Yu R; Gordon A; Colman-Lerner A
Curr Protoc Mol Biol; 2012 Oct; Chapter 14():Unit 14.18. PubMed ID: 23026908
[TBL] [Abstract][Full Text] [Related]
53. Adaptive tracking algorithm for trajectory analysis of cells and layer-by-layer assessment of motility dynamics.
Qureshi MH; Ozlu N; Bayraktar H
Comput Biol Med; 2022 Nov; 150():106193. PubMed ID: 37859286
[TBL] [Abstract][Full Text] [Related]
54. CP-CHARM: segmentation-free image classification made accessible.
Uhlmann V; Singh S; Carpenter AE
BMC Bioinformatics; 2016 Jan; 17():51. PubMed ID: 26817459
[TBL] [Abstract][Full Text] [Related]
55. Seeing Is Believing: Quantifying Is Convincing: Computational Image Analysis in Biology.
Sbalzarini IF
Adv Anat Embryol Cell Biol; 2016; 219():1-39. PubMed ID: 27207361
[TBL] [Abstract][Full Text] [Related]
56. 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]
57. Deep learning for cellular image analysis.
Moen E; Bannon D; Kudo T; Graf W; Covert M; Van Valen D
Nat Methods; 2019 Dec; 16(12):1233-1246. PubMed ID: 31133758
[TBL] [Abstract][Full Text] [Related]
58. Analyzing angiogenesis on a chip using deep learning-based image processing.
Choi DH; Liu HW; Jung YH; Ahn J; Kim JA; Oh D; Jeong Y; Kim M; Yoon H; Kang B; Hong E; Song E; Chung S
Lab Chip; 2023 Jan; 23(3):475-484. PubMed ID: 36688448
[TBL] [Abstract][Full Text] [Related]
59. pcnaDeep: a fast and robust single-cell tracking method using deep-learning mediated cell cycle profiling.
Gui Y; Xie S; Wang Y; Wang P; Yao R; Gao X; Dong Y; Wang G; Chan KY
Bioinformatics; 2022 Oct; 38(20):4846-4847. PubMed ID: 36047834
[TBL] [Abstract][Full Text] [Related]
60. Segmentation of occluded hematopoietic stem cells from tracking.
Mankowski WC; Winter MR; Wait E; Lodder M; Schumacher T; Naik SH; Cohen AR
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():5510-3. PubMed ID: 25571242
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]