Anusha Achuthan, Ts. Dr.

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  • Senior Lecturer

    Email :  This email address is being protected from spambots. You need JavaScript enabled to view it.

    Tel : +604 653 4755
    Fax : +604 653 3335
    Room : 606

    School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang

    Research Cluster

    Data to Knowledge



  • Research Interest

    Computer Vision, Image Processing, Artificial Intelligence, Machine Learning, Deep Learning, Computational Intelligence

    Specialization

    Computer Vision, Medical Image Analysis, Brain Imaging, Computational Intelligence, Machine Learning

Qualifications

B.Comp Sci (USM), M.Sc (USM), Ph.D (USM) 

 

Interests

Computer Vision, Image Processing, Artificial Intelligence, Machine Learning, Deep Learning, Computational Intelligence

 

Projects

1. Fully Automated Segmentation of Tumor Regions on Different MRI Image-weighted Using 2D Convolutional Neural Networks in Osteosarcoma, Transdisciplinary Research University Grant Scheme (Rutrans), RM 116,306.00, 01/03/2024 - 28/02/2027, (Principal Investigator).

2. AI-Enabled Smart Surveillance For Unattended Baggage Detection, External Agency (Industry/Private-Sunway Shared Services Sdn Bhd), Rm 12,300.00, 01/11/2023 - 31/10/2024, (Principal Investigator).

3. Design and Adaptation of Digital Technologies to Deliver an Evidence-, Needs-based Health Care Services System for Ageing Malaysian (ENHance-M) Using A Gig Economy, Research University Team (Ru Team), RM 60,080.00, 01/01/2023 - 31/12/2024, (Principal Investigator).

4. Atlas-guided Interval Type-2 Fuzzy Model for Clinically Relevant Tractography Selection from Diffusion Tensor Imaging, FRGS, RM78,969.00, 01/09/2019-30/11/2022 (Principal Investigator).

5. Knowledge Guided Segmentation of Hippocampus in Brain Magnetic Resonance Images from Public Repositories,USM Short Term, RM33,000.00, 01/08/2017-31/07/2019 (Principal Investigator).

6. Automatic Localisation of Subcortical Structures in Brain magnetic Resonance Images using Point Set Registration, USM Postgraduate Research Grant, Mei 2013- Feb 2015 (Principal Investigator).

7. Micro-Credentials For Life-Long Learning And Employability: Building Capacities For Developing Agile Educational Interventions In Southeast Asian Universities (Microcasa), External Agency (Erasmus+), RM 799,941.00, 01/03/2023 - 28/02/2026 (Co Researcher).

8. Radiation-induced Polymerization in Polymer Gel Dosimeter embedded with Zinc Oxide Nanoparticles for Radiotherapy Treatment Dose Verification, FRGS, RM130,200.00, 07/09/2021-06/09/2024 (Co Researcher).

9. High-pass Domain Kernel in Bilateral Filter to Enhance Small Blood Vessel Segmentation of Magnetic Resonance Angiography (MRA) Data Sets for Cerebral Small Vessel Disease (CSVD) Detection, FRGS, RM71,700.00, 07/09/2021-06/09/2023 (Co Researcher).

10. Development and Application of MyExerGames Apps: Promoting Healthy Lifestyle via Smartphone-Based Exercise Intervention Among Sedentary Population, RUI USM, RM60,000.00, 01/09/2020-28/02/2025 (Co Researcher).

11. Image Data Analytics For Industry 4.0 (P08C1-20), CREST Grant, RM 206,500.00, 01/01/2021 - 31/12/2022 (Co Researcher).

12. Elucidating The Role of Brain-Derived Neurotrophic Factor (BDNF) Val66Met Gene Polymorphism As a Predictor for the Cognitive Performance of Aging Brain in Response to an 8-week of Wii-Exergames Training, FRGS, RM186,248.00, 01/09/2019-31/08/2022 (Co Researcher).

13. Image Stitching Algorithm For Machine Vision Inspection, Estek Automation Sdn Bhd, RM12,000.00, 27/01/2020-06/08/2020, (Co Researcher)14. Enhanced Nature Inspired Based Classification Algorithm for Medical Data Analysis, USM RUI, RM63,770.00, 01/09/2018-31/08/2020 (Co Researcher).

 

Publications

[Latest publications: Google Scholar]

1. Zhang C., Achuthan, A., Himel, G. M. S. (2024). State-of-the-Art and Challenges in Pancreatic CT Segmentation: A Systematic Review of U-Net and Its Variants. IEEE Access. 12: 78726-78742.1.

2. Achuthan, A., Yii, S. H., Alkhafaji, A., Mohammed, AF. (2024). MyPlate: A Diet Monitoring and Recommender Application. Malaysian Journal of Medicine & Health Sciences. 20(2): 196-203.

3. Fawzi, A., Achuthan, A., Belaton, B. (2022). Dominant Gray Level Based Particle Swarm Optimization Clustering for Segmenting Brain Tumor Sub-regions from Multimodal Magnetic Resonance Images. In: Alfred, R., Lim, Y. (eds) Proceedings of the 8th International Conference on Computational Science and Technology. Lecture Notes in Electrical Engineering. 835. Springer, Singapore.

4. Goni M. R., Ruhaiyem N. I. R., Mustapha M., Anusha A. and Che Mohd Nassir C. M. N. (2022). Brain Vessel Segmentation Using Deep Learning—A Review. IEEE Access. 10:111322-111336.

5. Fazili I., Anusha A., Mustapha M. and Bahari B (2022). Conceptual Framework for Optimized Pipeline Selection For BrainTractography Using Multi-Criteria Decision Analysis. 7th International Conference on Communication, Image and Signal Processing (CCISP), Chengdu, China. 541-545.

6. Safri A.A., Nassir C.M.N.C.M., Iman I.N., Mohd Taib N.H., Anusha A., Mustapha M. (2022). Diffusion tensor imaging pipelines measures of cerebral white matter integrity: An overview of recent advances and prospects. World Journal of Clinical Cases. 10(24):8450-8462.

7. Aminuddin N., Anusha A., Ruhaiyem N.I.R. et al. (2022). Reduced cerebral vascular fractal dimension among asymptomatic individuals as a potential biomarker for cerebral small vessel disease. Scientific Reports. 12:11780.

8. Muhammad K.A., Ibrahim L.S., Anusha A., Radin A N., Ahmad HZS, Noor Diyana O. (2022). Estimation of Pediatric Dose Descriptors Adapted to Individual Specific Size From CT Examinations. Radiation Protection Dosimetry. ncac163.

9. Anusha A., Ali F., Bahari B. (2021). Adaptive Clip Limit Tile Size Histogram Equalization for Non-Homogenized Intensity Images, IEEE Access. 9:164466-164492.

10. Anusha A., Ali F., Bahari B. (2021). Dominant Gray Level based Particle Swarm Optimization Clustering for Segmenting Brain Tumor Sub-regions from Multimodal Magnetic Resonance Images, Eighth International Conference on Computational Science and Technology, ICCST2021.

11. Anusha A., Ali F., Bahari B. (2021). Brain Image Segmentation in Recent Years: A Narrative Review. Brain Sciences. 11(8):1055.

12. Anusha A. and Mandava R. (2021). Segmentation of hippocampus guided by assembled and weighted coherent point drift registration. Journal of King Saud University-Computer and Information Sciences. 33(8):1008-1017.

13. Anusha A., Goh X. Y. and Hazwani A. Y. (2019). USM ExerHunt: A Building Image Recognition-Based Exergame, Malaysian Journal of Medicine and Health Sciences. 15(SUPP9).

14. Chung S. H., Gan K.H., Mandava R. and Anusha A. (2019). Liver Tumor Segmentation using Triplanar Convolutional Neural Network: A Pilot Study, Lecture Notes in Electrical Engineering, 10th International Conference on Robotics, Vision, Signal Processing and Power Applications. 547:607-614.

15. Anusha A. and Mandava R. (2018). Prior Integrated Segmentation for Brain Structures: A Review, Malaysian Journal of Medicine and Health Sciences. 14(SUPP1):190- 200.

16. Noor Diyana O., Nurul Fathin M. S., Anusha A., Halimatul Asma S., Abdul Aziz M. Z. and Ibrahim L. S. (2018). Evaluation of Two Sinogram Interpolation Methods for Metal Artefacts Reduction in Computed Tomography, 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), Sarawak, pp. 137-139.

17. Anusha A. and Mandava R. (2015). Hippocampus segmentation using locally weighted prior based level set, Proc. of SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), Singapore, December 9.

18. Anusha A., Mandava R. and Win Mar S. J. (2013). Hippocampus Localization Guided by Coherent Point Drift Registration Using Assembled Point Set, Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8073 LNAI:92- 102.

19. Anusha A., Mandava R., and Ramachandram D., Aziz M. E. and Shuaib I. L. (2010). Wavelet energy-guided level set-based active contour: A segmentation method to segment highly similar regions, Computers In Biology And Medicine. 40 (7):608-620.

20. Anusha A., Mandava R., and Ramachandram D., Aziz M. E. and Shuaib I. L. (2009). Wavelet Energy Guided Level Set for Segmenting Highly Similar Regions in Medical Images, 2nd International Conference on Biomedical Engineering and Informatics (BMEI'09), Tianjin, 17-19 October 2009.

21. Anusha A. and Mandava R. and Ramachandram D. (2006). Detection of Secondary Structure in Medical Images using Wavelet and Watershed, The 2nd Distributed Frameworks for Multimedia Applications, Pulau Pinang, May 2006.

 Teaching

  • CCS 513 Computer Vision & Image Processing (Computer Science, USM - Postgraduate)

  • CMT 322 Web Engineering & Technologies (Computer Science, USM - Undergraduate)

  • CPC 151 Fundamentals to Logic and Artificial Intelligence

  • MNucMed Medical Image Analysis (AMDI, USM - Postgraduate)

  • TCC 236/05 Data Structures and Algorithms (Wawasan Open University - Undergraduate)

  • Generative AI for Teaching and Learning

 MICROCREDENTIAL/MOOC

  1. Harnessing Generative AI for Teaching and Learning, USM, 2024.
  2. Fundamentals to AI, USM, 2023.
  3. Scientific Writing and Communication, 2018.

Recognition & Leadership

  • MOOC on Scientific Writing & Communication, 2018 USM Teaching & Learning Symposium, USM, Penang (Silver Award)
  • A Locally Integrated Shape-based Level Set Model for Segmenting Small Subcortical Brain Structures, The 9th International Conference on Digital Image Processing (ICDIP 2017), Hong Kong (Best Oral Presenter)

 

 

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School of Computer Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia
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  • Last Modified: Thursday 14 November 2024.