A general approach for segmenting elongated and stubby biological objects: Extending a chord length transform with the radon transform

2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Volumn , Issue , 2010, Pages 161-164

  Xue, Quan ^a   Jones, Nick S ^a   Leake, Mark C ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Chord length transform; High throughput; Image analysis; In vivo microscopy; Radon transform

Indexed keywords

BIOLOGICAL OBJECTS; CENTER-OF-MASS; CHORD LENGTHS; DIRECTIONAL INFORMATION; ESCHERICHIA COLI BACTERIA; GENERAL APPROACH; HIGH-THROUGHPUT; IN-VIVO; LENGTH SCALE; OBJECT BOUNDARIES; PRECISE POSITION; RADON TRANSFORM; RADON TRANSFORMED IMAGE; SEGMENTATION ALGORITHMS; THREE-DIMENSIONAL VOLUME; TIME-LAPSE MICROSCOPY; TWO-DIMENSIONAL IMAGES;

ASPECT RATIO; BACTERIA; BACTERIOLOGY; ESCHERICHIA COLI; IMAGE ANALYSIS; IMAGE SEGMENTATION; MEDICAL IMAGING; PRESSURE DROP; RADON; THROUGHPUT; WAVELET TRANSFORMS;

THREE DIMENSIONAL;

EID: 77955196799     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2010.5490388     Document Type: Conference Paper

References (13)

1. Pham, D. L., Xu, C.Y. and Prince, J.L.: Current Methods in Medical Image Segmentation. Annual Review of Biomedical Engineering, vol. 2, pp.315-337 (2000).
2. Roerdink, J.M. and Meijster, A.: The Watershed Transform: Definitions, Algorithms and Parallelization Strategies. Fundamenta Informaticae, vol 41, pp.187-228 (2000).
3. Carpenter, A.E., Jones, T.R., Lamprecht, M.R., Clarke, C., Kang, I., Friman, O., Guertin, D.A., Chang, J.H., Lindquist, R.A., Moffat, J., Golland, P. and Sabatini, D.M.: CellProfiler: Image Analysis for High Throughput Microscopy. http://www.cellprofiler.org.
4. Dzyubachyk, O., Niessen, W. & Meijering, E. Advanced Level-Set Based Multi-Cell Segmentation and Tracking in Time-Lapse Fluorescence Microscopy Images. IEEE International Symposium on Biomedical Imaging -ISBI 2008, 185-188. (2008).
5. EI-Baz, A.S. Faraq, A.A. Ei Munim, H.A. Yuksel, S.E. Level Set Segmentation Using Statistical Shape Priors. Computer vision and Pattern Recognition workshop, (CVPRW), pp.78-85. (2006).
6. Visen.N., Shashidhar.N., Paliwal.J., and Jayas.D.: Identification and Segmentation of Occluding Groups of Grain Kernels in a Grain Sample Image. Journal of Agricultural Engineering Research, vol. 79, pp. 159-166, (2001).
7. Kutalik.Z., Razaz.Moe., and Baranyi.J.: Occluding Convex Image Segmentation for E.coli Microscopy Images. XII. European Signal Processing Conference (EUSIPCO). Vienna, Austria. Pp.937-940. September, (2004).
8. Lerner.B., Guterman. H., and Dinstein.I.: A Classification-Driven Partially Occluded Object Segmentation (cpoos) Method with Application to Chromosome Analysis. IEEE Transactions on Signal Processing, vol.46, pp. 2841-2847, (1998).
9. Soille, P., Breen, E.J. and Jones, R.: Recursive Implementation of Erosions and Dilations along discrete lines at arbitrary angles. IEEE Trans. Pattern Anal.Mach.Intell. vol.18, pp 562-567, (1996).
10. Sandau, K. and Ohser, J.: The Chord Length transform and the Segmentation of Crossing Fibers. Journal of miscroscopy, vol.226. pp.43-53. Dec. (2007).
11. Deans, S. R.: The Radon Transform and Some of Its Applications. New York: John Wiley & Sons. (1983).
12. Giboa, G., Sochen, N. and Zeevi, Y.Y.: Image Enhancement and Denoising by Complex Diffusion Processes. IEEE Trans on Pattern Analysis and Machine intelligence, vol.26, pp.1020-1036. August (2004).
13. Kriete, A., Papazoglou, E., Edrissi, B., Pais, H., Pourrezaei, K. Automated Quantification of Quantum-Dot-Labelled Epidermal Growth Factor Receptor Internalization via Multiscale Image Segmentation. J Microscopy, vol. 2222, pp. 22-27. (2006).