Dr. Nisha Joseph

Dr. Nisha Joseph

Designation: Associate Professor

Education : B.Tech, M.Tech, Ph.D.

Professional Experience

Teaching: 16

Research: 4

Specialization:

UG: Computer Engineering

PG: Computer and Information Technology

PhD:  Computer Science and Engineering

Memberships:

ACM (6225485)

British Computer Society (995029518)

ISTE (LM 45237)

Internet Society (2217208)

IAENG (International Association of Engineers- 262842)

Chartered Engineer [India]

The Institution of Engineers(India- M 1711770)

Research Interests:

Medical Image processing

Machine Learning

Deep Learning

Patents:

  Granted: 

1.    Title: Cryptography Based Financial Analytical Tool through Artificial Intelligence

      File Number: 2021104023
      Country Filed: Australia
      Granted Date: 20/04/2022

2   Title: The Computer Aided Diagnosis (CAD) System for the Detection of Alzheimer Disease Using MRI Real Images.
      File Number: 2021101725
      Country Filed: Australia
      Granted Date: 05/05/2021

Published: 

   1.Title of Invention: Covid Tracker,

      The Patent Office Journal No. 51/2020 Dated 18/12/2020

   2.Title of invention:Cryptography Based Financial Analytical Tool Through Artificial Intelligence,

      The Patent Office Journal No. 35/2020 Dated 28/08/2020

Publications:

International Journals

  1. “Segmentation and Calculation of Volume of Tumor on MRI using Efficient Feature Extraction Techniques”, International Journal of Pharmaceutical Research DOI: https://doi.org/10.31838/ijpr/2020.12.04.595 http://www.ijpronline.com/ViewArticleDetail.aspx?ID=19163
  2. Study on Evaluation of Machine Learning Approaches in Brain Tumor MR Images”, Turkish Journal of Computer and Mathematics Education(2021).
  3. “The Role of Educational Technologies in CSR Perception of Tourism Education: The Comparative Analysis of E-Learning and M-Learning Tools as Moderators”, Journal of Risk and Financial  Management https://doi.org/10.3390/jrfm13120318
  4. “Patient Specific Brain Tumor Segmentation using Context Sensitive Feature Extraction in MR Images”, International Journal of Computing and Digital Systems,(2020), DOI:https://dx.doi.org/10.12785/ijcds/090607,  ISSN (2210-142X) https://journal.uob.edu.bh/handle/123456789/3912
  5. “ A Novel Efficient Deep Feature Extractor and Classifier Approach for Brain Tumor Segmentation in Magnetic Resonant Images”, Bioscience Biotechnology Research Communications ,2020), DOI: http://dx.doi.org/10.21786/bbrc/13.4/57
  6. “Brain Tumor segmentation using Deep Convolution Neural Network and Support Vector Machine”, Journal of Critical Reviews, (2020), DOI: 31838/jcr.07.19.71, ISSN- 2394-5125, http://www.jcreview.com/?mno=102762       http://www.jcreview.com/fulltext/197-1594889473.pdf?1597918122 
  7. “Brief Survey on MRI Brain Image Segmentation Using Image Processing Techniques” , International Journal of Advances in Computer Science and Technology (2020), ISSN 2320 – 2602 http://www.warse.org/IJACST/static/pdf/file/ijacst22972020.pdf 
  8. ”Deep Weber Dominant Local Order Based Feature Generator and Improved Convolution Neural Network for Brain Tumor Segmentation in MR Images”, International Journal of Engineering and Advanced Technology, (2020) DOI: 10.35940/ijeat.C4702.029320, ISSN: 2249-8958 (Online), Volume-9 Issue-3, Page No. 3150-3157.   https://www.ijeat.org/wp-content/uploads/papers/v9i3/C4702029320.pdf
  9. “Adaptive Multi-Threshold Based De-noising Filter for Medical Image Applications” –International Journal of Computational Vision and Robotics, (2019), Vol.9,No.3, https://www.inderscience.com/info/inarticle.php?artid=99439    DOI: 10.1504/IJCVR.2019.099439
  10. “Survey on Image De-noising Based on Two- Stage Median Filtering Approach”- International Journal of Advanced Research in Computer Engineering & Technology, (2017) Volume 6, Issue 9.http://ijarcet.org/wp-content/uploads/IJARCET-VOL-6-ISSUE-9-1494-1498.pdf
  11. “Compression of Color images using clustering techniques”- IJSER –International Journal of Scientific and Engineering Research, (2013), Volume 4, Issue 8. https://www.ijser.org/onlineResearchPaperViewer.aspx?Compression-of-Color-Images-Using-Clustering-Techniques.pdf
  12. “Advanced encoder for scanned multifaceted manuscripts using clustering techniques” International Journal of CSE and IT research, (2013), Volume 3, Issue 2 June.
  13. “Image compression using clustering techniques” –International Journal of CSE and IT research,March(2013) 

 International Conference

  1. “ A Brief Survey on MRI Brain Image Segmentation Using Image Processing Techniques”, ICCIDT-2020 at Managalam College of Engineering, Kottayam.
  2. “A Research Study on Brain Tumor Detection Techniques”, Proceedings, International Conference on Communication and Artificial Intelligence, Springer,  2022.
  3. “Performance Comparison of Brain Tumor Segmentation Algorithms”, Proceedings,Advances in Computational Intelligence and Communication Technology,Springer 2022
  4. ” Patient Specific Tumor Detection using Convolution Neural Network”,International Conference on artificial Intelligence and Machine Learning,2022.
  5. ” Performance Comparison of Classifiers of MR Brain Tumor Images on Various Datasets”, IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems,2022.
  6. ”Texture and Deep Feature Extraction in Brain Tumor Segmentation using Hybrid ensemble Classifier”,Internationalm Conference on Computational Intelligence for Engineering and Management Applications(CIEMA),2022.
  7. “ Dual Threshold Adaptive Filter Cascaded with Cuckoo Search optimization Technique to maximize the Peak Signal ratio for Denoising the Mammogram Image”, International E-Conference on Electrical, Communication and Computing(2020) at Tagore Engineering College,  Chennai.
  8. “Performance Study on Brain Tumor Segmentation Techniques”, IEEE International Conference on Computing Communication and Automation at Galgotias University, (2018) Greater Noida, Delhi NCR, India. https://ieeexplore.ieee.org/document/8777660
  9. “Comparative Study on Fully Automatic Supervised Machine Learning Techniques for Brain Tumor Segmentation in MR Images”, International Conference on Emerging Trends and Challenges in Science and Arts 2018 (ICETC 2018) at NPR Arts and Science College on 28th December 2018. 

National Conference

  1. “Data mining integration with relational databases” (2009), National Conference on Frontier Research Areas in Computing.

Achievements:

Gate Qualified(2011  – 90 percentile)

Contact Details:

     GSM: +91 9847223135

     Email: nisha.joseph@saintgits.org