Personnel Profile

Dr. Ayush Goyal, Visiting Assistant Professor of Computer Science Engineering

Dr. Ayush Goyal

DrAyush Goyal has a Ph.D. in Computer Science from the University of Oxford, which he completed in the year 2013. He graduated in Electrical Engineering from Boise State University, where he graduated as a Top Ten Scholar with a 4.0 / 4.0 GPA and one of the top four Eta Kappa Nu Engineering Honor Society honorable mentions in the year 2005. He is a Clarendon Scholar, having won the prestigious Clarendon scholarship award to pursue his doctoral studies at Oxford. He has done two post-doctoral research projects from Tulane University and King's College London, published more than 25 journal and conference papers, and filed 4 patents.
His research projects are in applying machine learning and big data analysis algorithms for applications in computer vision, image processing, and biomedical engineering, in which he is mentoring undergraduate and graduate research student projects. He has worked on feature extraction, region / object of interest segmentation, and 3D reconstruction and modeling of cardiac and brain MRI and CT images for computerized reconstruction of gray and white matter regions in the brain or blood vessels and the left ventricle in the heart. He is currently working on projects for developing computational software platforms as cardiac or neurological disease detection and decision support systems that facilitate fully automated extraction, segmentation, and measurement of left and right ventricles from cardiac MRI images and gray and white matter regions, lesions, tumors, etc. from brain MRI images.
 
His technical background and research experience are in the field of computer vision, image processing, biomedical engineering, particularly biomedical image processing and bioinformatics. His Oxford doctoral research was in the area of biomedical image processing for 3D computational reconstructions of coronary vasculature. The image data used was cardiac MRI, CT, and whole-organ optical fluorescence cryomicrotomography. His post-doctoral research in King's College London was in cardiac MRI image processing for reconstruction of patient-specific computational models of coronary arteries and the left and right ventricles for evaluation of a patient’s heart using clinical parameters such as ejection fraction, stroke volume, and end-systolic and end-diastolic volume. His post-doctoral research at Tulane University was in protein design bioinformatics using computational modeling of proteins for minimizing their energy and optimizing the protein sequence, with applications in HIV protease inhibitors and drug delivery to targeted cancer cells. One of his biomedical research projects has been in the field of medical image processing applied to automatic detection of mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smears of patients and designing a stand-alone independent portable minilab bacilliscope for screening tuberculosis from stained sputum, urine, and blood smears of patients. In another medical image processing research, he has also been working on automatic segmentation of the gray and white matter regions from brain MRI and endo and epi cardia of the left and right ventricles and the myocardium from cardiac MRI images. The motivation for this research is quantifying clinical parameters such as atrophy rate as a measure of dementia or neurological imapirment in the brain in order to assess brain disease and ejection fraction, left ventricle myocardium mass, stroke volume, systolic volume, and diastolic volume in the heart in order to assess a patient's heart disease. One of his latest medical image processing research work is in segmentation, extraction, and reconstruction of computational models of aneurysms, stenosis, and occlusions from MRI and CT images and computational fluid dynamics based blood flow simulations through computational models of these vascular anomalies for prediction of stroke in a patient’s coronary or cerebral vasculature. His latest medical image processing research is in automatic detection of disease from pattern recognition of dried blood microdrop stains using support vector machine learning algorithms that when trained can detect the difference between the dried blood stain patterns of normal and diseased individuals.

Publications

Journal Publications

  1. Goyal, A., Lee, J., Lamata, P., van den Wijngaard, J., van Horssen, P., Spaan, J., & Smith, N. P. “Model-based vasculature extraction from optical fluorescence cryomicrotome images.” IEEE Transactions on Medical Imaging, vol. 32, no. 1, pp. 56-72, 2013.
  2. Michler, C., Cookson, A. N., Chabiniok, R., Hyde, E., Lee, J., Sinclair, M., Sochi, T., Goyal, A., Vigueras, G., Nordsletten, D.A., Smith, N.P. “A computationally efficient framework for the simulation of cardiac perfusion using a multicompartment Darcy porousmedia flow model.” International Journal for Numerical Methods in Biomedical Engineering, vol. 29, no. 2, pp. 217-232, 2013.
  3. Hyde, E.R., Cookson, A.N., Lee, J., Michler, C., Goyal, A., Sochi, T., Chabiniok, R., Sinclair, M., Nordsletten, D.A., Spaan, J., van den Wijngaard, J.P.H.M., Siebes, M., & Smith, N.P. “Multi-Scale Parameterisation of a Myocardial Perfusion Model Using Whole-Organ Arterial Networks.” Annals of Biomedical Engineering, vol. 42, no. 4, pp. 797-811, 2014.
  4. Sikarwar, B.S., Roy, M.K., Ranjan, P., Goyal, A., “Automatic Disease Screening Method Using Image Processing for Dried Blood Microfluidic Drop Stain Pattern Recognition”, Journal of Medical Engineering and Technology Vol. 40, No. 5, pp. 245-254, 2016.
  5. Sikarwar, B.S., Roy, M.K., Ranjan, P., Goyal, A. "Imaging-Based Method for Precursors of Impending Disease from Blood Traces." Advances in Intelligent Systems and Computing Vol. 468, pp. 411-424, Springer, 2016.
  6. Sikarwar, B.S., Roy, M.K., Ranjan, P., Goyal, A. "Automatic Pattern Recognition for Detection of Disease from Blood Drop Stain Obtained with Microfluidic Device." Advances in Intelligent Systems and Computing, Vol. 425, pp. 655-667. Springer, 2015.
  7. Bhan, A., Bathla, D., Goyal, A. “Patient-Specific Cardiac Computational Modeling Based on Left Ventricle Segmentation from Magnetic Resonance Images.” Advances in Intelligent Systems and Computing Vol. 469, pp. 179-187, Springer, 2016.
  8. Ray, V., Goyal, A. “Automatic Left Ventricle Segmentation in Cardiac MRI Images Using a Membership Clustering and Heuristic Region-Based Pixel Classification Approach.” Advances in Intelligent Systems and Computing, Vol. 425, pp. 615-623. Springer, 2015.
  9. Agarwal, P., Kahlon, S.S., Bisht, N., Dash, P., Ahuja, S. and Goyal, A., “Abandoned Object Detection and Tracking Using CCTV Camera.” Lecture Notes in Networks and Systems, Vol. 10, pp. 483-492. Springer, 2017.
  10. Chhabra, M., and Goyal, A. “Accurate and Robust Iris Recognition Using Modified Classical Hough Transform.” Lecture Notes in Networks and Systems, Vol. 10, pp. 493-507. Springer, 2017.
  11. Goyal, A., Ray, V. “Belongingness Clustering and Region Labeling Based Pixel Classification for Automatic Left Ventricle Segmentation in Cardiac MRI Images.” Translational Biomedicine, Vol. 6, Issue 3, 2015.
  12. Goyal, A., Roy, M., Gupta, P., Dutta, M. K., Singh, S., Garg, V. “Automatic Detection of Mycobacterium tuberculosis in Stained Sputum and Urine Smear Images.” Archives of Clinical Microbiology, Vol. 6, Issue 3, 2015.

Conference Papers

  1. Goyal, A., van den Wijngaard, J., van Horssen, P., Grau, V., Spaan, J., Smith, N. “Intramural spatial variation of optical tissue properties measured with fluorescence microsphere images of porcine cardiac tissue.” Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1408-1411, 2009.
  2. Duta, M., Thiyagalingam, J., Trefethen, A., Goyal, A., Grau, V., & Smith, N. “Parallel simulation for parameter estimation of optical tissue properties.” In Euro-Par 2010-Parallel Processing (pp. 51-62), 2010.
  3. Bhan, A., Goyal, A., Chauhan, N. & Wang, C.W. “Feature Line Profile Based Automatic Detection of Dental Caries in Bitewing Radiography.” International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE), pp. 635-640, IEEE, 2016.
  4. Bhan, A., Goyal, A., & Ray, V. “Fast Fully Automatic Multiframe Segmentation of Left Ventricle in Cardiac MRI Images Using Local Adaptive K-Means Clustering and Connected Component Labeling.” 2nd International Conference on Signal Processing and Integrated Networks (SPIN), pp. 114-119, IEEE, 2015.
  5. Bhan, A., Goyal, A., Dutta, M.K., Sankhla, D., Khanna, P., Travieso, C.M., & Hernandez, J.B.A. “Left ventricle wall extraction in cardiac MRI using region based level sets and vector field convolution.” 4th International Work Conference on Bioinspired Intelligence (IWOBI), pp. 133-138, IEEE, 2015.
  6. Bhan, A., Goyal, A., Dutta, M.K., Riha, K., Omran, Y. “Image-Based Pixel Clustering and Connected Component Labeling in Left Ventricle Segmentation of Cardiac MR Images.” 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 339-342, IEEE, 2015.
  7. Ray, V., Goyal, A. "Image based sub-second fast fully automatic complete cardiac cycle left ventricle segmentation in multi frame cardiac MRI images using pixel clustering and labelling." 8th International Conference on Contemporary Computing (IC3), pp. 248-252, IEEE, 2015.
  8. Ray, V., Goyal, A. “Image-Based Fuzzy C-Means Clustering And Connected Component Labeling Subsecond Fast Fully Automatic Complete Cardiac Cycle Left Ventricle Segmentation In Multi Frame Cardiac Mri Images.” International Conference on Systems in Medicine and Biology (ICSMB), IEEE, 2015.
  9. Sharma, P., Sharma, S., Goyal, A. “An MSE (mean square error) based analysis of deconvolution techniques used for deblurring/restoration of MRI and CT Images.” 2nd International Conference on Information and Communication Technology for Competitive Strategies (ICTCS-2016), March 04-05, 2016, Udaipur, India, Conference Proceedings by ACM – ICPS Proceedings Vol. ISBN 978-1-4503-3962-9/16/03, DOI: http://dx.doi.org/10.1145/2905055.2905257, 2016.
  10. Goyal, A., Bathla, D., Sharma, P., Sahay, M., Sood, S. “MRI Image Based Patient Specific Computational Model Reconstruction of the Left Ventricle Cavity and Myocardium.” 2016 International Conference on Computing, Communication and Automation (ICCCA), pp. 1065-1068, IEEE, 2016.
  11. Roy, M., Sikarwar, B.S., Goyal, A. “Design and Fabrication of A Microfluidic Device For Measuring Surface Tension of Biological Fluid.” Indian International Science Festival (IISF), IIT Delhi, 4-8th December, 2015.
  12. Roy, M., Sikarwar, B.S., Prakash, R., Ranjan, P. Goyal, A. “Parametric Study of Ball and Socket Joint for Bio-Mimicking Exoskeleton.” 17th International Conference on Foot and Ankle Biomechanics (ICFAB), International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering, World Academy of Science, Engineering, and Technology (WASET), 2015.
  13. Sikarwar, B.S., Roy, M., Goyal, A., Ranjan, P. “Innovative Screening Tool Based on Physical Properties of Blood.” 17th International Conference on Biomechanics, Biophysics and Bioengineering (ICBBB), International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering, World Academy of Science, Engineering, and Technology (WASET), 2015.
  14. Roy, M.K., Goyal, A., Kumar, V. “Ecoflush-Wastewater Recycling And Rainwater Harvesting Toilet Flush System.” 1st International Conference on Advancements and Recent Innovations in Mechanical, Production, and Industrial Engineering (ARIMPIE 2015), ELK Asia Pacific Journals – Special Issue, 2015.

Contact Information

Electrical Engineering and Computer Science
EC 306
MSC 192 Texas A&M University-Kingsville
Kingsville, Texas 78363-8202
voice: (361) 593-2630
fax: (361) 593-4026
email: ayush.goyal@tamuk.edu
Personal Website: https://www.linkedin.com/in/ayush-goyal-83906219/

This page was last updated on: March 26, 2018