Dr. Md. Kamrul Hasan

Education

  • PhD, Chiba University, Japan.
  • MEng, Chiba University, Japan.
  • MSc (EEE), Bangladesh University of Engineering and Technology, Bangladesh
  • BSc (EEE), Bangladesh University of Engineering and Technology, Bangladesh

 

Research Interests

Digital Signal Processing, Speech and Image Processing, Adaptive Filtering, Biomedical Signal Processing, Medical Imaging, Elastography, Quantitative Ultrasound.

 

Work Experience

Professor (2004), Associate Professor (2001), Assistant Professor (1989),
Department of Electrical and Electronic Engineering
Bangladesh University of Engineering and Technology
Dec 1989 – Present
Professor of International Scholar, Department of Biomedical Engineering,
Kyung Hee University, Korea
Apr 2010, Jun 2011, Sep 2012, Jun 2013
Invited Research Fellow,
Department of Information and Communication Engineering
The University of Tokyo, Japan
Dec 2011, Oct 2006
Invited Research Professor, Department of Information and Computer Sciences
Chiba University, Japan
Dec 2007 – Feb 2008
Visiting Researcher, Imperial College London, UK,
Department of Electrical and Electronic Engineering
Aug 2004 – April 2005

 

Professional Services

  • Associate Editor: IEEE Access

 

Publication Search

Google scholar | Full list of publications

 

Patents

  1. S.Y. LEE and M. K. Hasan, “Apparatus for removing ring artifact in an X-ray CT (Computed Tomography) and a removing method thereof capable of revising the pixel value of a defective cell,” Korean Patent ID: 1020110125696, 22 Nov. 2011.

 

Selected Publications by Area

 

Elastography (Strain Imaging)

  1. G. Kibria and M. K. Hasan, “A class of kernel based real-time elastography algorithms”, Ultrasonics, vol.61, pp.88-102, 2015.
  2. Nahiyan and M. K. Hasan, “Hybrid algorithm for elastography to visualize both solid and fluid filled lesions”, Ultrasound in Medicine and Biology, vol. 41, no.4, pp.1058-1078, 2015.
  3. A. Hussain, F. Alam, S. A. Rupa, R. Awaal, S. Y. Lee, and M. K. Hasan, “Lesion edge preserved direct average strain estimation for ultrasound elasticity imaging”, Ultrasonics, vol. 54, no. 1, pp. 137-146, 2014.
  4. S. R. Ara, F. Mohsin, F. Alam, S. A. Rupa, R. Awaal, S. Y. Lee, and M. K. Hasan, “Phase-based direct average strain estimation for elastography”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 60, no. 11, pp.2266-2283, 2013.
  5. K. Hasan, E. M. A. Anas, S. K. Alam, and S. Y. Lee, “Direct mean strain estimation for elastography using nearest-neighbor weighted least-squares approach in the frequency domain”, Ultrasound in Medicine and Biology, vol. 38, no. 10, pp.1759-1777, 2012.
  6. A. Hussain, E. M. A. Anas, S. K. Alam, S. Y. Lee, and M. K. Hasan, “Direct and gradient based average strain estimation by using weighted nearest neighbor cross-correlation peaks”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 59, no. 8, pp.1713-1728, 2012.
  7. A. Hussain, E. M. A. Anas, S. K. Alam, S. Y. Lee, and M. K. Hasan, “Robust Strain-Estimation Algorithm Using Combined Radiofrequency and Envelope Cross-Correlation with Diffusion Filtering”, Ultrasonic Imaging, vol. 34, pp.93-109, 2012.

Quantitative Ultrasound

  1. K. Hasan, M. S. E. Rabbi, and S. Y. Lee, “Blind deconvolution of ultrasound images using l1-norm-constrained block-based damped variable step-size multichannel LMS algorithm”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, in press, 2016.
  2. S. R. Ara, F. Alam, M. H. Rahman, S. Akther, R. Awaal, and M. K. Hasan, “Bi-modal multi-parameter based approach for benign-malignant classification of breast tumors”, Ultrasound in Medicine and Biology, vol.41, no.7, pp.2022-2038, 2015.
  3. K. Hasan, M. A. Hussain, S. R. Ara, S. Y. Lee, and S. K. Alam, “Using nearest neighbors for accurate estimation of ultrasonic attenuation in the spectral domain”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 60, no. 6, pp.1098-1114, 2013.

Magnetic Resonance Imaging (MRI)

  1. K. Bashar and M. K. Hasan, “Empirical mode decomposition based GRAPPA reconstruction algorithm for parallel MRI”, Biomed. Phys. Eng. Express, 1, 045006, 2015.

CT Imaging

  1. A. Haque, M. O. Ahmad, M. N. S. Swamy, M. K. Hasan, and S. Y. Lee, “Adaptive projection selection for computed tomography”, IEEE Trans. Image Processing, vol. 22, no. 12, pp.5085-5095, 2013.
  2. Rashid, S. Y. Lee, and M. K. Hasan, “An improved method for the removal of ring artifacts in high resolution CT imaging”, EURASIP Journal on Advances in Signal Processing, Elsevier, vol. 2012:93, 2012.
  3. M. A. Anas, S. Y. Lee and M. K. Hasan, “High quality 3-D correction of ring and radiant artifacts in flat panel detector based cone beam volume CT imaging”, Physics in Medicine and Biology, IOP, vol.56, no.19, pp.6495-6519, 2011.
  4. M. A. Anas, S. Y. Lee and M. K. Hasan, “Comparison of ring artifact removal methods using flat panel detector based CT images”, Biomedical Engineering Online, 10:72, doi:10.1186/1475-925X-10-72, 2011.
  5. N. M. Ashrafuzzaman, S. Y. Lee and M. K. Hasan, “A self-adaptive approach for the detection and correction of stripes in the sinogram: Suppression of ring artifacts in CT imaging”, EURASIP Journal on Advances in Signal Processing, Elsevier,doi:10.1155/2011/183547, Volume 2011, Jan. 2011.
  6. M. K. Hasan, F. Sadi, and S. Y. Lee, “Removal of ring artifacts in micro-CT imaging using iterative morphological filter”, DOI 10.1007/s11760-010-0170-z, Signal, Image and Video Processing (SIViP), Springer (UK), Published online, June, 2010.
  7. F. Sadi, S. Y. Lee, and M. K. Hasan, “Removal of ring artifacts in computed tomographic imaging using iterative center weighted median filter”, vol. 40, no. 1, pp.109-118, Computers in biology and medicine, Elsevier, Jan. 2010.
  8. M. A. Anas, S. Y. Lee and M. K. Hasan, “Removal of ring artifacts in CT imaging through detection and correction of stripes in the sinogram”, Physics in Medicine and Biology, IOP, vol. 55, pp.6911-6930, 2010.

Electrocardiogram (ECG) Analysis

  1. A. Arafat, A. W. Chowdhury, and M. K. Hasan, “A simple time domain algorithm for the detection of ventricular fibrillation in electrocardiogram”, Signal, Image and Video Processing (SIViP), Springer (UK), vol.5, pp.1-10, 2011.
  2. M. A. Anas and M. K. Hasan, “Exploiting correlation of ECG with certain EMD functions for ventricular fibrillation detection”, Computers in biology and medicine, Elsevier, vol. 41, pp.110-114, 2011.
  3. M. A. Anas and M. K. Hasan, “Sequential algorithm for ventricular tachycardia and fibrillation identification based on mean signal strength and low-order EMD functions”, Biomedical Engineering online (UK), DOI: 10.1186/1475-925X-9-43, 9:43, 2010.
  4. A. Arafat, J. Sieed, and M. K. Hasan, “Detection of ventricular fibrillation using empirical mode decomposition and Bayes decision theory”, vol. 39, no. 11, pp.1051-1057, Computers in biology and medicine, Elsevier, Nov. 2009.
  5. A. Haque, M. K. Hasan and H. Tazawa, “Investigation of the nonlinearity in the heart rate dynamics”, Medical Engineering & Physics, Elsevier Science B.V., vol.27, no.2, pp.27-31, 2001.