Abstract
We propose a simple and fast method for microscopy image enhancement and quantitatively evaluate its performance on a database containing cell images obtained from microscope setups of several levels of quality. The method utilizes an efficiently and accurately estimated relative modulation transfer function to generate images of higher quality, starting from those of lower quality, by filtering in the Fourier domain. We evaluate the method visually and based on correlation coefficient and normalized mutual information. We conclude that enhanced images exhibit high similarity, both visually and in terms of information content, with acquired high quality images. This is an important result for the development of a cost-effective screening system for cervical cancer.
Chapter PDF
Similar content being viewed by others
Keywords
- Point Spread Function
- Cervical Cancer Screening
- Optical Setup
- Normalize Mutual Information
- Fourier Domain
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Blinn, J.: Jim Blinnâs Corner: Dirty Pixels. Morgan Kaufmann Publishers Inc. (1998)
Forster, B., Van de Ville, D., Berent, J., Sage, D., Unser, M.: Extended depth-of-focus for multi-channel microscopy images: A complex wavelet approach. In: IEEE Int. Symp. Biomed. Imaging: Macro to Nano, vols. 1 and 2, pp. 660â663 (2004)
Guizar-Sicairos, M., Thurman, S.T., Fienup, J.R.: Efficient subpixel image registration algorithms. Optics Letters 33(2), 156â158 (2008)
Joshi, N., Szeliski, R., Kriegman, D.: PSF estimation using sharp edge prediction. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1â8. IEEE (2008)
Khare, A., Tiwary, U.S., Jeon, M.: Daubechies complex wavelet transform based multilevel shrinkage for deblurring of medical images in presence of noise. International Journal of Wavelets, Multiresolution and Information Processing 7(05), 587â604 (2009)
Lindblad, J., Sladoje, N., Malm, P., Bengtsson, E., Moshavegh, R., Mehnert, A.: Optimizing optics and imaging for pattern recognition based screening tasks. In: Proc. Int. Conf. on Pattern Recogn., Stockholm, Sweden, pp. 3333â3338, August 2014
Malm, P.: Image Analysis in Support of Computer-Assisted Cervical Cancer Screening. Ph.D. thesis, Uppsala University, Department of Information Technology (2013)
Malm, P.: Multi-resolution cervical cell dataset. Tech. Rep. 37. Uppsala University, Division of Visual Information and Interaction (2013)
Oliveira, J.P., Bioucas-Dias, J.M., Figueiredo, M.A.: Adaptive total variation image deblurring: a majorization-minimization approach. Signal Processing 89(9), 1683â1693 (2009)
Osher, S., Burger, M., Goldfarb, D., Xu, J., Yin, W.: An iterative regularization method for total variation-based image restoration. Multiscale Modeling & Simulation 4(2), 460â489 (2005)
Reddy, B., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. IEEE Transactions on Image Processing 5(8), 1266â1271 (1996)
Smith, E.H.B.: PSF estimation by gradient descent fit to the ESF. In: Electronic Imaging 2006, pp. 60590Eâ60590E. International Society for Optics and Photonics (2006)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600â612 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Âİ 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Lindblad, J., Bengtsson, E., Sladoje, N. (2015). Microscopy Image Enhancement for Cost-Effective Cervical Cancer Screening. In: Paulsen, R., Pedersen, K. (eds) Image Analysis. SCIA 2015. Lecture Notes in Computer Science(), vol 9127. Springer, Cham. https://doi.org/10.1007/978-3-319-19665-7_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-19665-7_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19664-0
Online ISBN: 978-3-319-19665-7
eBook Packages: Computer ScienceComputer Science (R0)