Anu Shaju Areeckal

About

Dr. Anu Shaju Areeckal pursued B.Tech. degree in Electronics and Communication Engineering (ECE) from Mahatma Gandhi University, Kerala, India in 2010, and M.Tech. degree in VLSI Design from Karunya University, Tamil Nadu, India in 2012. She received her Ph.D. degree from National Institute of Technology Karnataka (NITK), Surathkal, India in March 2019, for her research work on 'Early diagnosis of Osteoporosis using metacarpal radiogrammetry and texture analysis'. Her research areas of interest are Image processing, Computer vision, Machine learning, Deep learning and VLSI design.

Employment

• Manipal Institute of Technology, MAHE Assistant professor
  2019 - Present
• Holy Grace Academy of Engineering for Women Assistant Professor
  2012 - 2014

Education

• National Institute of Technology Karnataka PhD
  2014 - 2019
• Karunya University M.Tech
  2010 - 2012
• Mar Baselios Christian College of Engineering and Technology Kuttikanam B.Tech
  2006 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• A Novel Deep Learning Pipeline for Vertebra Labeling and Segmentation of Spinal Computed Tomography Images
  IEEE Access 2024 DOI: 10.1109/access.2024.3358874
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• Star identification in night sky images using mobile phone camera
  2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES) 2022 DOI: 10.1109/spices52834.2022.9774242
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• A web-based application for face detection in real-time images and videos
  Journal of Physics: Conference Series 2022 DOI: 10.1088/1742-6596/2161/1/012071
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• Detection of fraudulent credit card transactions: A comparative analysis of data sampling and classification techniques
  Journal of Physics: Conference Series 2022 DOI: 10.1088/1742-6596/2161/1/012072
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• Performance analysis of texture characterization techniques for lung nodule classification
  Journal of Physics: Conference Series 2022 DOI: 10.1088/1742-6596/2161/1/012045
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• Semi-automated estimation of spinal curvature from scoliosis radiographs using difference matrix
  2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) 2020 DOI: 10.1109/discover50404.2020.9278054
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• Current and Emerging Diagnostic Imaging-Based Techniques for Assessment of Osteoporosis and Fracture Risk
  IEEE Reviews in Biomedical Engineering 2019 DOI: 10.1109/rbme.2018.2852620
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• Cortical Volumetry Using 3D Reconstruction of Metacarpal Bone from Multi-View Images
  4th IEEE International Conference on Recent Advances in Computational Systems (RAICS), India 2018 DOI: 10.1109/raics.2018.8635067
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• Combined radiogrammetry and texture analysis for early diagnosis of osteoporosis using Indian and Swiss data
  Computerized Medical Imaging and Graphics, Elsevier 2018 DOI: 10.1016/j.compmedimag.2018.05.003
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• Early diagnosis of osteoporosis using radiogrammetry and texture analysis from hand and wrist radiographs in Indian population
  Osteoporosis International, Springer Nature 2018 DOI: 10.1007/s00198-017-4328-1
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