HIGH DYNAMIC RANGE IMPLEMENTATION ON ACUTE LEUKEMIA SLIDE IMAGES

Authors

  • Toh Leow Bin Electronic & Biomedical Intelligent Systems (EBItS) Research Group, School of Mechatronics Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • M.Y. Mashor Electronic & Biomedical Intelligent Systems (EBItS) Research Group, School of Mechatronics Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • Phaklen Ehkan School of Computer and Communication Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • H. Rosline Department of Hematology, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
  • A.K. Junoh Electronic & Biomedical Intelligent Systems (EBItS) Research Group, School of Mechatronics Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia
  • N.H. Harun Electronic & Biomedical Intelligent Systems (EBItS) Research Group, School of Mechatronics Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia

DOI:

https://doi.org/10.11113/jt.v77.6223

Keywords:

Acute leukemia diagnosis, high dynamic range imaging

Abstract

Conventional diagnosis of acute leukemia is based on examining the morphology of the blood and bone marrow smear under the microscope and the process can be tedious, time intensive and highly skilled resources dependent. Over recent years, features fusion techniques base on statistical and morphological features had been explored in computer vision studies to enhance the capability of acute leukemia diagnosis task. However, microscopic image capture from the light microscope usually has poor quality due to the limited dynamic range of the camera. Thus, image regions with intensity levels outside the dynamic range captured by the camera sensor suffer from lack of details, appearing either underexposed or overexposed. This paper proposed a High Dynamic Range (HDR) imaging techniques to solve the problem of limited dynamic range and enhance the morphological features of blast cells. The proposed method consists of two main parts: implementing HDR techniques on acute leukemia slide images and comparing the dynamic range between HDR image and original images with different exposure time based on the intensity histograms obtained. The results presented showed that the HDR implementation has enhanced the morphological features of blast cells and increase the dynamic range, hence may benefit in the feature extraction and classification process of acute leukemia.

References

B. S. Eastwood and E. C. Childs. 2012. Image Alignment For Multiple Camera High Dynamic Range Microscopy. Applications of Computer Vision (WACV), 2012 IEEE Workshop. 225–232.

N. H. Harun, N. R. Mokhtar, M. Y. Mashor, H. Adilah, R. Adollah, N. Mustafa, N. F. M. Nasir, and H. Roseline. 2008. Color Image Enhancement Techniques Based On Partial Contrast And Contrast Stretching For Acute Leukaemia Images, 2008 Internation Conference on Postgraduate Education (ICPE). Penang, Malaysia

N. R. Mokhtar, N. H. Harun, M. Y. Mashor, H. Roseline, N. Mustafa, and R. Adollah. 2009. Image Enhancement Techniques Using Local , Global , Bright, Dark and Partial Contrast Stretching For Acute Leukemia Images, 2009 Proceeding of World Congress on Engineering. I: 3–8.

A. N. A. Salihah, M. Y. Mashor, N. H. Harun, and H. Rosline. 2010. Colour Image Enhancement Techniques For Acute Leukaemia Blood Cell Morphological Features, Syst. Man Cybern. (SMC), 2010 IEEE Int. Conf. 3677-3682.

N. Hazwani, A. Halim, M. Y. Mashor, and H. Rosline. 2012. Image Enhancement Technique for Bone Marrow. 929–934.

A. N. A. Salihah, M. Y. Mashor, N. H. Harun, A.A Abdullah and H. Rosline. 2010. Improving Colour Image Segmentation on Acute Myelogenous Leukemia Images Using Contrast Enhancement Techniques. 2010 IEEE EMBS Conference on Biomedical Engineering & Sciences (IECBES 2010). Kuala Lumpur, Malaysia. 246-251.

P. E. Debevec and J. Malik. 2008. Recovering High Dynamic Range Radiance Maps From Photographs 2008. ACM SIGGRAPH 2008 Classes. 31.

E. Reinhard, G. Ward, S. Pattanaik, and P. Debevec. 2006 High Dynamic Range Imaging. Elsevier.

G.W. Larson, H. Rushmeier, and C. Piatko. 1997. A Visibility Matching Tone Reproduction Operator For High Dynamic Range Scenes. Visualization and Computer Graphics, IEEE Transactions. 3(4): 291–306.

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Published

2015-11-11

Issue

Section

Science and Engineering

How to Cite

HIGH DYNAMIC RANGE IMPLEMENTATION ON ACUTE LEUKEMIA SLIDE IMAGES. (2015). Jurnal Teknologi, 77(6). https://doi.org/10.11113/jt.v77.6223