Towards high performance cell segmentation in multispectral fine needle aspiration cytology of thyroid lesions

Computer Methods and Programs in Biomedicine

Volumn 98, Issue 3, 2010, Pages 231-240

  Gabriel, Edgar ^a   Venkatesan, Vishwanath ^a   Shah, Shishir ^a  

^a University of Houston   (United States)

Author keywords

Fine needle aspiration cytology; Image analysis; Multi core processors; Parallel computing; PC clusters

Indexed keywords

FINE NEEDLE ASPIRATION CYTOLOGY; FINE-NEEDLE ASPIRATIONS; MULTI-CORE PROCESSOR; PARALLEL COMPUTING; PC CLUSTERS;

CELLS; CYTOLOGY; IMAGE ANALYSIS; NEEDLES; PARALLEL ARCHITECTURES; PIXELS;

DIAGNOSIS;

ARTICLE; ASPIRATION BIOPSY; AUTOMATION; CELL FUNCTION; CELL SEGMENTATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; CYTOLOGY; IMAGE ANALYSIS; IMAGE SEGMENTATION; MATHEMATICAL ANALYSIS; MEMORY CONSOLIDATION; PERFORMANCE MEASUREMENT SYSTEM; THYROID DISEASE;

BIOPSY, FINE-NEEDLE; CYTOLOGICAL TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; SUBCELLULAR FRACTIONS; THYROID NEOPLASMS;

EID: 77952743830     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2009.07.008     Document Type: Article

References (42)

1. Hegedus L. The thyroid nodule. New Eng. J. Med. 2004, 351:1764-1771.
2. Gharib H., Goellner J.R. Fine-needle aspiration of the thyroid: an appraisal. Ann. Intern. Med. 1993, 118:282-289.
3. Association T.A.T. Thyroid fine needle aspiration (FNA) and cytology. Consensus Guidelines for Thyroid Testing in the New Millennium, vol. 6 2003, 1-80.
4. Shah S., Schwartz M.R., Mody D.R., Scheiber-Pacht M., Amrikachi M. The role of multispectral microscopy in differentiating benign and malignant thyroid nodules: a pilot study of 24 cases. Proceedings of the Annual Meeting of the United States and Canadian Academy of Pathology 2008.
5. Feng C., Shuzhen C., Libo Z. New abnormal cervical cell detection method of multi-spectral pap smears. Wuhan Univ. J. Nat. Sci. 2007, 12:476-480.
6. Shah S., Thigpen J., Merchant F., Castleman K. Photometric calibration for automated multispectral imaging of biological samples. Proceedings of the 1st Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI, Copenhagen) 2006, 27-33. D. Metaxas, R. Whitaker, J. Rittscher, T. Sebastian (Eds.).
7. Farkas D., Ballou B., Fisher F., Fishman D. Microscopic and mesoscopic spectral bio-imaging. Proceedings of SPIE, vol. 2678 1996, 200-209.
8. Ornberg R.L., Woerner M., Edwards D.A. Analysis of stained objects in histopathological sections by spectral imaging and differential absorption. J. Histochem. Cytochem. 1999, 47:1307-1313.
9. Wu H., Barba J., Gil J. A parametric fitting algorithm for segmentation of cell images. IEEE Trans. Biomed. Eng. 1998, 45:400-407.
10. Castleman K.R. Digital Image Processing 1979, Prentice Hall.
11. Wu H.S., Berba J., Gil J. Iterative thresholding for segmentation of cells from noisy images. J. Microsc. 2000, 179:296-304.
12. Meas-Yedid V., Tilie S., Olivo-Marin J.C. Color image segmentation based on Markov random field clustering for histological image analysis. ICPR'02: Proceedings of the 16th International Conference on Pattern Recognition (ICPR'02), vol. 1 2002, 10796.
13. Sahoo P.K., Soltani S., Wong A.K.C. A survey of thresholding techniques. Comput. Vis. Graph. Image Process. 1988, 41:233-260.
14. Lie W. Automatic target segmentation by locally adaptive image thresholding. IEEE Trans. Image Process. 1995, 4:1036-1041.
15. Ser P., Siu W. Novel detection of conics using 2-D Hough planes. IEEE Proc. Vision, Image Signal Processing, vol. 142 1995, 262-270.
16. Vincent L., Soille P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Mach. Intell. 1991, 13:583-598.
17. Adiga P.U., Chaudhuri B. An efficient method based on watershed and rule-based merging for segmentation of 3-d histo-pathological images. Pattern Recognit. 2001, 34:1449-1459.
18. Cheng X., Zhou X., Wong T. Automated segmentation, classification and tracking of cancer cell nuclei in time-lapse microscopy. IEEE Trans. Biomed. Eng. 2006, 53:762-766.
19. Hartigan J.A., Wong M.A. A K-means clustering algorithm. Appl. Stat. 1979, 28:100-108.
20. Faugeras O.D., Pratt W.K. Decorrelation methods of texture feature extraction. IEEE Trans. Pattern Anal. Mach. Intell. 1980, 2:323-332.
21. Bamford P., Lovell B. Unsupervised cell nucleus segmentation with active contours. Signal Process. 1998, 71:203-213.
22. Kurugollu F., Sankur B. Color cell image segmentation using pyramidal constraint satisfaction neural network. IAPR Workshop on Machine Vision Applications 1998, 85-88.
23. Ferrer-Roca O., Gomez J.A.P., Estevez M. Chromatin texture from hematoxylin stained thyroid lesions. Anal. Cell. Pathol. 1998, 17:209-217.
24. Yogesan K., Jorgensen T., Albregtsen F., Tveter K.J., Danielsen H.E. Entropy-based texture analysis of chromatin structure in advanced prostate cancer. Cytometry 1996, 24:268-276.
25. K.I. Laws, Textured Image Segmentation, PhD thesis, 1980.
26. Tourassi G.D., Frederick E.D., Vittitoe N.F., Coleman R.E. Fractal texture analysis of perfusion lung scans. Comput. Boimed. Res. 2000, 33:161-171.
27. Shah S., Aggarwal J.K. A Bayesian segmentation framework for textured visual images. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 1997, 1014-1020.
28. Ablameyko S., Nedzved A., Lagunovsky D., Patsko O., Kirillov V. Cell image segmentation: review of approaches. Proc. ICPR, vol. 2 2001, 26-34.
29. Choudhary A., Ranka S. Guest editor's introduction: parallel processing for computer vision and image understanding. Computer 1992, 25:7-10.
30. Braunl T., Feyrer S., Raph W., Reinhardt M. Parallel Image Processing 2001, Springer.
31. Braunl T. Tutorial in data parallel image processing. Aust. J. Intell. Inf. Process. Syst. 2001, 6:164-174.
32. Squyres J.M., Lumsdaine A., Stevenson R.L. A toolkit for parallel image processing. Proceedings of the SPIE Conference on Parallel and Distributed Methods for Image Processing 1998, 69-80.
33. Monnes P., Furht B. Parallel JPEG algorithms for still image compression. Proceedings of the 1994 IEEE Southeast Conference 'Creative Technology Transfer, A Global Affair' 1994, 375-379.
34. Fatemi H., Corporaal H., Basten T., Jonker P., Kleihorst R. Implementing face recognition using a parallel image processing environment based on algorithmic skeletons. 10th Annual Conference of the Advanced School for Computing and Imaging, Proceedings 2004, 351-357. J.J. van Wijk, J.W.J. Heijnsdijk, K.G. Langedoen, R. Veltkamp (Eds.).
35. Nicolescu C., Jonker P. A data and task parallel image processing environment. Parallel Comput. 2002, 28:945-965.
36. Hoefler T., Schellmann M., Gorlatch S., Lumsdaine A. Communication optimization for medical image reconstruction algorithms. Recent Advances in Parallel Virtual Machine and Message Passing Interface, 15th European PVM/MPI Users' Group Meeting, vol. LNCS 5205 2008, 75-83. Springer.
37. Manjunath B.S., Ma W. Texture features for browsing and retrieval of image data. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI - Special issue on Digital Libraries) 1996, 18:837-842.
38. Message Passing Interface Forum: MPI: A Message Passing Interface Standard, 1995, http://www.mpi-forum.org/.
39. Board O.A.R. OpenMP Application Program Interface, Version 2.5 2005.
40. Frigo M., Johnson S.G. The Design and Implementation of FFTW3. Proc. IEEE 2005, 93:216-231.
41. Malony A.D., Shende S., Bell R., Li K., Li L., Trebon N. Advances in the tau performance system. Perform. Anal. Grid Comput. 2004, 129-144.
42. Gabriel E., Fagg G.E., Bosilca G., Angskun T., Dongarra J.J., Squyres J.M., Sahay V., Kambadur P., Barrett B., Lumsdaine A., Castain R.H., Daniel D.J., Graham R.L., Woodall T.S. Open MPI: goals, concept, and design of a next generation MPI implementation. Proceedings, 11th European PVM/MPI Users' Group Meeting 2004, 97-104.