Envisaging Through Artificial Intelligence : GIAN

Envisaging Through Artificial Intelligence : GIAN

Manisha Rath | Oct 16, 2017

  • 0

Recently the enthralling and fascinating seminar on Artificial intelligence for Magnetic Resonance Brain Image Processing under GIAN, organized by the Department of Computer Science and Engineering was initiated. It is 10 days long seminar which has started since 9th October. The programme is being efficiently coordinated by Dr Bansidhar Majhi and Dr Ratnakar Dash. The seminar was inaugurated on 9th October by Prof K.K. Mohapatra, Dean (Academics) and Prof. A.K.Panda, Dean SRICCE. GIAN Co-ordinator S.K.Sahoo, International Faculty Dr Yudong Zhang from School of Computer Nanjing Normal University, China and course co-ordinators Dr Bansidhar Majhi and Dr Ratnakar Dash at the Conference Hall of CS Department, were the other notable personalities present on the dais.

The Government Of India introduced a new programme titled Global initiative of academic networks(GIAN) in higher education aimed at tapping the talent pool of scientists and entrepreneurs, internationally to encourage their engagement with the institutes of higher education in India so as to augment the country's existing academic resources,accelerate the pace of quality reform and elevate India's scientific and technological capacity to global excellence. This seminar on Artificial intelligence for MR Brain image processing is being funded by Ministry of Human Resources and Development(MHRD) of India under GIAN.

The seminar would be focussing on the following aspects:

  • Fundamentals of brain Magnetic Resonance Imaging(MRI)
  • Preprocessing techniques in MRI
  • Feature extraction techniques (wavelet and its variants, curvelet, ripplet etc)
  • Fundamental of AritificaI Intelligence(AI) techniques( ANN, Non- Parallel SVM, Parallel SVM, etc)
  • Advanced AI techniques( Extreme learning machine, kernel ELM, evolutionary ELM, etc)
  • Autoencoder, sparse autoencoder, stacked autoencoder, convolutional neural network

Around 76 students of Ph.D., M.Tech and B.Tech from various institutes of India are a part of this seminar. The seminar has been planned aptly to have two hours of lecture followed by two hours tutorial every day.

Day 1

The inaugural day began with the lecture of the international faculty Dr Yudong Zhang on Comparison of Neuroimaging modalities: X-ray, CT, Ultrasound, PET, SPECT, and MRI, the reason for MRI being the 21st-century neuroimaging tool and the preprocessing steps of MR images. In the evening session, i.e. from 4-6pm, a tutorial was taken by Dr Yudong Zhang which focussed on the use of FMRIB Software Library (FSL) to implement 3D brain image extraction, segmentation, and normalization.

Day 2

On the second day, there was a lecture on Diffusion Magnetic Resonance Imaging Processing and analysis, the comparison between diffusion tensor model and ball-&-stick model that was delivered by Dr Yudong Zhang. This was followed by a tutorial on the use of FSL to implement tract-based spatial statistics (TBSS) and model-based statistics (Part – I) in the evening session by the international faculty.

Day 3

The third day was set in motion with the lecture of Dr Yudong Zhang on Function MRI processing, single-session analysis, and group analysis. Then there was a tutorial on the use of FSL to implement tract-based spatial statistics (TBSS) and model-based statistics (Part – II).

Day 4

The fourth day commenced with lecture of Dr. Yudong Zhang that focussed on extracting the region-of-interest (ROI) from human brains, manually or automatically, wavelet entropy that is a powerful tool to extract brain features, advanced wavelet analysis, stationary wavelet transform, wavelet packet transform, dual-tree complex wavelet transform, and Tsallis entropy (Part – I). It was followed by a tutorial on using Matlab 2017a (Wavelet Design & Analysis Toolbox) to implement feature extraction from brain images by Dr Yudong Zhang.

Day 5

The fifth day was triggered with another lecture by Dr Yudong Zhang on decision tree and k-nearest neighbours (k-NN) for pathological brain detection, Support vector machine (SVM) and parallel versus nonparallel (Part – I). Succeeding it was a tutorial on Use of Matlab 2017a (Classification Learner Toolbox) to implement pathological brain detection (Part – I).

Team Monday Morning caught up with Prof. Ratnakar Dash one of the course coordinators. On being asked about the seminar he said,

This seminar is being conducted under the GIAN Scheme of the MHRD under GOI and it has provided the students a golden opportunity to have a productive discussion with the international faculties and consult them in a particular research area.

Team MM will bring you the details of the other half of the program in the next issue. Please stay tuned for the same.


    Leave a comment

    Login to comment.
    Ask a Question Admission Forum