Iterative thresholding for segmentation of cells from noisy images

We introduce an iterative thresholding algorithm for the segmentation of cells from noisy cell images. The thresholding image, which is initially a constant, changes iteratively with both the previous segmentation and image local activity. Experimental results for both synthesized and real cell images are provided to demonstrate the performance of the algorithm.

[1]  Hai-Shan Wu,et al.  An efficient semi‐automatic algorithm for cell contour extraction , 1995 .

[2]  J. Barba,et al.  A parametric fitting algorithm for segmentation of cell images , 1998, IEEE Transactions on Biomedical Engineering.

[3]  Hai-Shan Wu,et al.  Region growing segmentation of textured cell images , 1996 .

[4]  Haisang Wu,et al.  Optimal segmentation of cell images , 1998 .

[5]  M. Celenk.  Colour image segmentation by clustering , 1991 .

[6]  P. Cohen,et al.  A fuzzy clustering approach to texture segmentation , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[7]  Vir V. Phoha,et al.  Image recovery and segmentation using competitive learning in a layered network , 1996, IEEE Trans. Neural Networks.

[8]  Hai-Shan Wu,et al.  An algorithm for noisy cell contour extraction via area merging , 1994 .

[9]  Chin-Tu Chen,et al.  Constraint satisfaction neural networks for image recognition , 1993, Pattern Recognit..

[10]  Sebastiano B. Serpico,et al.  Multisensor data fusion by a region-based approach , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[11]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Thrasyvoulos N. Pappas.  An adaptive clustering algorithm for image segmentation , 1992, IEEE Trans. Signal Process..

[13]  Suchendra M. Bhandarkar,et al.  Integrating edge and surface information for range image segmentation , 1992, Pattern Recognit..

[14]  J. Barba,et al.  Nuclear diffuseness as a measure of texture: Definition and application to the computer‐assisted diagnosis of parathyroid adenoma and carcinoma , 1994, Journal of microscopy.

[15]  Yianni Attikiouzel,et al.  Model-based region growing segmentation of textured images , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[16]  K. E. Tait,et al.  Image recovery using the anisotropic diffusion equation , 1996, IEEE Trans. Image Process..

[17]  HAI‐SHAN WD,et al.  An iterative algorithm for cell segmentation using short‐time Fourier transform , 1996, Journal of microscopy.

[18]  James C. Bezdek,et al.  A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain , 1992, IEEE Trans. Neural Networks.

[19]  I. Sethi,et al.  Thresholding based on histogram approximation , 1995 .

[20]  Jake K. Aggarwal,et al.  The integration of region and edge-based segmentation , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[21]  Seong-Dae Kim,et al.  Image flow segmentation and estimation using displaced spatial gradient , 1992 .