241 related articles for article (PubMed ID: 26835962)
1. Automated tracking of temporal displacements of a red blood cell obtained by time-lapse digital holographic microscopy.
Moon I; Yi F; Rappaz B
Appl Opt; 2016 Jan; 55(3):A86-94. PubMed ID: 26835962
[TBL] [Abstract][Full Text] [Related]
2. Three-dimensional counting of morphologically normal human red blood cells via digital holographic microscopy.
Yi F; Moon I; Lee YH
J Biomed Opt; 2015 Jan; 20(1):016005. PubMed ID: 25567613
[TBL] [Abstract][Full Text] [Related]
3. Automated statistical quantification of three-dimensional morphology and mean corpuscular hemoglobin of multiple red blood cells.
Moon I; Javidi B; Yi F; Boss D; Marquet P
Opt Express; 2012 Apr; 20(9):10295-309. PubMed ID: 22535119
[TBL] [Abstract][Full Text] [Related]
4. Automated quantitative analysis of 3D morphology and mean corpuscular hemoglobin in human red blood cells stored in different periods.
Moon I; Yi F; Lee YH; Javidi B; Boss D; Marquet P
Opt Express; 2013 Dec; 21(25):30947-57. PubMed ID: 24514667
[TBL] [Abstract][Full Text] [Related]
5. Recognition and classification of red blood cells using digital holographic microscopy and data clustering with discriminant analysis.
Liu R; Dey DK; Boss D; Marquet P; Javidi B
J Opt Soc Am A Opt Image Sci Vis; 2011 Jun; 28(6):1204-10. PubMed ID: 21643406
[TBL] [Abstract][Full Text] [Related]
6. Automated three-dimensional tracking of living cells by digital holographic microscopy.
Langehanenberg P; Ivanova L; Bernhardt I; Ketelhut S; Vollmer A; Dirksen D; Georgiev G; von Bally G; Kemper B
J Biomed Opt; 2009; 14(1):014018. PubMed ID: 19256706
[TBL] [Abstract][Full Text] [Related]
7. Quantitative investigation of red blood cell three-dimensional geometric and chemical changes in the storage lesion using digital holographic microscopy.
Jaferzadeh K; Moon I
J Biomed Opt; 2015 Nov; 20(11):111218. PubMed ID: 26502322
[TBL] [Abstract][Full Text] [Related]
8. A practical criterion for focusing of unstained cell samples using a digital holographic microscope.
Malik R; Sharma P; Poulose S; Ahlawat S; Khare K
J Microsc; 2020 Aug; 279(2):114-122. PubMed ID: 32441768
[TBL] [Abstract][Full Text] [Related]
9. Lossless and lossy compression of quantitative phase images of red blood cells obtained by digital holographic imaging.
Jaferzadeh K; Gholami S; Moon I
Appl Opt; 2016 Dec; 55(36):10409-10416. PubMed ID: 28059271
[TBL] [Abstract][Full Text] [Related]
10. Human red blood cell recognition enhancement with three-dimensional morphological features obtained by digital holographic imaging.
Jaferzadeh K; Moon I
J Biomed Opt; 2016 Dec; 21(12):126015. PubMed ID: 28006044
[TBL] [Abstract][Full Text] [Related]
11. Comparative study of human erythrocytes by digital holographic microscopy, confocal microscopy, and impedance volume analyzer.
Rappaz B; Barbul A; Emery Y; Korenstein R; Depeursinge C; Magistretti PJ; Marquet P
Cytometry A; 2008 Oct; 73(10):895-903. PubMed ID: 18615599
[TBL] [Abstract][Full Text] [Related]
12. Automated segmentation of multiple red blood cells with digital holographic microscopy.
Yi F; Moon I; Javidi B; Boss D; Marquet P
J Biomed Opt; 2013 Feb; 18(2):26006. PubMed ID: 23370481
[TBL] [Abstract][Full Text] [Related]
13. 3D morphometry of red blood cells by digital holography.
Memmolo P; Miccio L; Merola F; Gennari O; Netti PA; Ferraro P
Cytometry A; 2014 Dec; 85(12):1030-6. PubMed ID: 25242067
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Microdeformation of RBCs under oxidative stress measured by digital holographic microscopy and optical tweezers.
Liu J; Zhu L; Zhang F; Dong M; Qu X
Appl Opt; 2019 May; 58(15):4042-4046. PubMed ID: 31158157
[TBL] [Abstract][Full Text] [Related]
16. Cell morphology-based classification of red blood cells using holographic imaging informatics.
Yi F; Moon I; Javidi B
Biomed Opt Express; 2016 Jun; 7(6):2385-99. PubMed ID: 27375953
[TBL] [Abstract][Full Text] [Related]
17. AI-based analysis of 3D position and orientation of red blood cells using a digital in-line holographic microscopy.
Kim Y; Kim J; Seo E; Lee SJ
Biosens Bioelectron; 2023 Jun; 229():115232. PubMed ID: 36963327
[TBL] [Abstract][Full Text] [Related]
18. Cell shape identification using digital holographic microscopy.
Zakrisson J; Schedin S; Andersson M
Appl Opt; 2015 Aug; 54(24):7442-8. PubMed ID: 26368783
[TBL] [Abstract][Full Text] [Related]
19. Imaging bacterial 3D motion using digital in-line holographic microscopy and correlation-based de-noising algorithm.
Molaei M; Sheng J
Opt Express; 2014 Dec; 22(26):32119-37. PubMed ID: 25607177
[TBL] [Abstract][Full Text] [Related]
20. A robust algorithm for segmenting and tracking clustered cells in time-lapse fluorescent microscopy.
Tarnawski W; Kurtcuoglu V; Lorek P; Bodych M; Rotter J; Muszkieta M; Piwowar Ł; Poulikakos D; Majkowski M; Ferrari A
IEEE J Biomed Health Inform; 2013 Jul; 17(4):862-9. PubMed ID: 25055315
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
