Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets

PLoS Biology

Volumn 14, Issue 1, 2016, Pages

  Belevich, Ilya ^a   Joensuu, Merja ^a,b   Kumar, Darshan ^a   Vihinen, Helena ^a   Jokitalo, Eija ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

^b UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAM; ELECTRON MICROSCOPY; IMAGE PROCESSING; MICROSCOPY; QUANTITATIVE ANALYSIS; SOFTWARE;

IMAGE PROCESSING, COMPUTER-ASSISTED; MICROSCOPY; SOFTWARE;

EID: 84961335080     PISSN: 15449173     EISSN: 15457885     Source Type: Journal    
DOI: 10.1371/journal.pbio.1002340     Document Type: Article

References (41)

1. Knott G, Genoud C, Is EM dead? Journal of cell science. 2013;126(Pt 20):4545–52. doi: 10.1242/jcs.124123 24124192.
2. Lidke DS, Lidke KA, Advances in high-resolution imaging—techniques for three-dimensional imaging of cellular structures. Journal of cell science. 2012;125(Pt 11):2571–80. doi: 10.1242/jcs.090027 22685332; PubMed Central PMCID: PMC3706075.
3. Schneider CA, Rasband WS, Eliceiri KW, NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9(7):671–5. doi: 10.1038/nmeth.2089 22930834.
4. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9(7):676–82. doi: 10.1038/Nmeth.2019 WOS:000305942200021.
5. Kankaanpää P, Paavolainen L, Tiitta S, Karjalainen M, Päivärinne J, Nieminen J, et al. BioImageXD: an open, general-purpose and high-throughput image-processing platform. Nat Methods. 2012;9(7):683–9. doi: 10.1038/nmeth.2047 22743773.
6. Kremer JR, Mastronarde DN, McIntosh JR, Computer visualization of three-dimensional image data using IMOD. Journal of structural biology. 1996;116(1):71–6. doi: 10.1006/jsbi.1996.0013 8742726.
7. Sommer C, Straehle C, Kothe U, Hamprecht FA, Ilastik: Interactive Learning and Segmentation Toolkit. I S Biomed Imaging. 2011:230–3. WOS:000298849400054.
8. Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magnetic resonance imaging. 2012;30(9):1323–41. doi: 10.1016/j.mri.2012.05.001 22770690; PubMed Central PMCID: PMC3466397.
9. Belevich I, Joensuu M, Kumar D, Vihinen H, Jokitalo E. Microscopy Image Browser 2015. http://mib.helsinki.fi.
10. Puhka M, Joensuu M, Vihinen H, Belevich I, Jokitalo E, Progressive sheet-to-tubule transformation is a general mechanism for endoplasmic reticulum partitioning in dividing mammalian cells. Molecular biology of the cell. 2012;23(13):2424–32. doi: 10.1091/mbc.E10-12-0950 22573885; PubMed Central PMCID: PMC3386207.
11. Joensuu M, Belevich I, Rämö O, Nevzorov I, Vihinen H, Puhka M, et al. ER sheet persistence is coupled to myosin 1c-regulated dynamic actin filament arrays. Molecular biology of the cell. 2014;25(7):1111–26. doi: 10.1091/mbc.E13-12-0712 24523293; PubMed Central PMCID: PMC3967974.
12. Anttonen T, Belevich I, Kirjavainen A, Laos M, Brakebusch C, Jokitalo E, et al. How to bury the dead: elimination of apoptotic hair cells from the hearing organ of the mouse. Journal of the Association for Research in Otolaryngology: JARO. 2014;15(6):975–92. doi: 10.1007/s10162-014-0480-x 25074370; PubMed Central PMCID: PMC4389953.
13. Anttonen T, Kirjavainen A, Belevich I, Laos M, Richardson WD, Jokitalo E, et al. Cdc42-dependent structural development of auditory supporting cells is required for wound healing at adulthood. Scientific reports. 2012;2:978. doi: 10.1038/srep00978 23248743; PubMed Central PMCID: PMC3523287.
14. Furuta KM, Yadav SR, Lehesranta S, Belevich I, Miyashima S, Heo JO, et al. Plant development. Arabidopsis NAC45/86 direct sieve element morphogenesis culminating in enucleation. Science. 2014;345(6199):933–7. doi: 10.1126/science.1253736 25081480.
15. Dettmer J, Ursache R, Campilho A, Miyashima S, Belevich I, O'Regan S, et al. CHOLINE TRANSPORTER-LIKE1 is required for sieve plate development to mediate long-distance cell-to-cell communication. Nature communications. 2014;5:4276. doi: 10.1038/ncomms5276 25008948.
16. Majaneva M, Remonen I, Rintala JM, Belevich I, Kremp A, Setälä O, et al. Rhinomonas nottbecki n. sp. (Cryptomonadales) and Molecular Phylogeny of the Family Pyrenomonadaceae. The Journal of eukaryotic microbiology. 2014;61(5):480–92. doi: 10.1111/jeu.12128 24913840.
17. Belevich I, Kumar D, Vihinen H. Microscopy Image Browser, on-line tutorials 2015. http://mib.helsinki.fi/tutorials.html.
18. Linkert M, Rueden CT, Allan C, Burel JM, Moore W, Patterson A, et al. Metadata matters: access to image data in the real world. The Journal of cell biology. 2010;189(5):777–82. doi: 10.1083/jcb.201004104 20513764; PubMed Central PMCID: PMC2878938.
19. Perona P, Malik J, Scale-Space and Edge-Detection Using Anisotropic Diffusion. Ieee T Pattern Anal. 1990;12(7):629–39. doi: 10.1109/34.56205 WOS:A1990DK89400002.
20. Kroon DJ, Slump CH, Maal TJJ, Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. Medical Image Computing and Computer-Assisted Intervention—Miccai 2010, Pt Iii. 2010;6363:221–8. doi: 10.1007/978-3-642-15711-0_28 WOS:000287945600028.
21. Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Susstrunk S, SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell. 2012;34(11):2274–82. doi: 10.1109/TPAMI.2012.120 22641706.
22. Frangi AF, Niessen WJ, Vincken KL, Viergever MA, Multiscale vessel enhancement filtering. Medical Image Computing and Computer-Assisted Intervention—Miccai'98. 1998;1496:130–7. WOS:000082115900014.
23. Perez AJ, Seyedhosseini M, Deerinck TJ, Bushong EA, Panda S, Tasdizen T, et al. A workflow for the automatic segmentation of organelles in electron microscopy image stacks. Frontiers in neuroanatomy. 2014;8:126. doi: 10.3389/fnana.2014.00126 25426032; PubMed Central PMCID: PMC4224098.
24. Helmstaedter M, Briggman KL, Turaga SC, Jain V, Seung HS, Denk W, Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature. 2013;500(7461):168–74. doi: 10.1038/nature12346 23925239.
25. Sommer C, Gerlich DW, Machine learning in cell biology—teaching computers to recognize phenotypes. Journal of cell science. 2013;126(Pt 24):5529–39. doi: 10.1242/jcs.123604 24259662.
26. Breiman L, Random forests. Mach Learn. 2001;45(1):5–32. doi: 10.1023/A:1010933404324 WOS:000170489900001.
27. Kaynig V, Fuchs T, Buhmann JM, Neuron Geometry Extraction by Perceptual Grouping in ssTEM Images. Proc Cvpr Ieee. 2010:2902–9. doi: 10.1109/Cvpr.2010.5540029 WOS:000287417502122.
28. Jones C, Liu T, Cohan NW, Ellisman M, Tasdizen T, Efficient semi-automatic 3-D segmentation for neuron tracing in electron microscopy images. Journal of neuroscience methods. 2015;246:13–21. doi: 10.1016/j.jneumeth.2015.03.005 25769273; PubMed Central PMCID: PMC4398646.
29. Lucchi A, Smith K, Achanta R, Knott G, Fua P, Supervoxel-based segmentation of mitochondria in em image stacks with learned shape features. IEEE transactions on medical imaging. 2012;31(2):474–86. doi: 10.1109/TMI.2011.2171705 21997252.
30. Boykov Y, Kolmogorov V, An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans Pattern Anal Mach Intell. 2004;26(9):1124–37. doi: 10.1109/TPAMI.2004.60 15742889.
31. Couprie C, Grady L, Najman L, Talbot H, Power Watersheds: A Unifying Graph-Based Optimization Framework. IEEE Trans Pattern Anal Mach Intell. 2010. doi: 10.1109/TPAMI.2010.200 21079274.
32. Mishchenko Y, A fast algorithm for computation of discrete Euclidean distance transform in three or more dimensions on vector processing architectures. SIViP. 2015;9(1):19–27. doi: 10.1007/s11760-012-0419-9
33. Sage D, Prodanov D, J.-Y. T, Schindelin J. MIJ: Making Interoperability Between ImageJ and Matlab Possible. ImageJ User & Developer Conference; Luxembourg2012.
34. Schmid B, Schindelin J, Cardona A, Longair M, Heisenberg M, A high-level 3-D visualization API for Java and ImageJ. Bmc Bioinformatics. 2010;11:274. doi: 10.1186/1471-2105-11-274 20492697; PubMed Central PMCID: PMC2896381.
35. Nicastro D, Schwartz C, Pierson J, Gaudette R, Porter ME, McIntosh JR, The molecular architecture of axonemes revealed by cryoelectron tomography. Science. 2006;313(5789):944–8. doi: 10.1126/science.1128618 WOS:000239817000036.
36. Drishti: volume exploration and presentation tool. http://sf.anu.edu.au/Vizlab/drishti.
37. Peng H, Ruan Z, Long F, Simpson JH, Myers EW, V3-D enables real-time 3-D visualization and quantitative analysis of large-scale biological image data sets. Nature biotechnology. 2010;28(4):348–53. doi: 10.1038/nbt.1612 20231818; PubMed Central PMCID: PMC2857929.
38. MathWorks. File exchange. http://www.mathworks.se/matlabcentral/fileexchange/.
39. Ichihara YG, Okabe M, Iga K, Tanaka Y, Musha K, Ito K, Color Universal Design—The selection of four easily distinguishahle colors for all color vision types. Proc Spie. 2008;6807. doi: 10.1117/12.765420 WOS:000255639200023.
40. Brewer C, Harrower M, Sheesley B, Woodruff A, Heyman D. ColorBrewer 2.0 2013. http://colorbrewer2.org/.
41. Allan C, Burel JM, Moore J, Blackburn C, Linkert M, Loynton S, et al. OMERO: flexible, model-driven data management for experimental biology. Nat Methods. 2012;9(3):245–53. doi: 10.1038/nmeth.1896 22373911; PubMed Central PMCID: PMC3437820.