APAJI INSTITUTE OF MATHEMATICS & APPLIED COMPUTER TECHNOLOGY BANASTHALI UNIVERSITY DIPLOMA IN MEDICAL IMAGE PROCESSING Tentative break up of topics
Objective: The objective of this course shall be to provide students with an overview of the computational and mathematical methods in medical image processing, which is essential for their development of research skills. The course shall cover the main sources of medical imaging data (CT, MRI, PET, and ultrasound). We shall discuss many of the current methods used to enhance and extract useful information from medical images. A variety of radiological diagnostic scenarios shall be used as examples to motivate the research methods. Theory Time : 7 to 8 PM (Fri., Sat. Sun. Mon.)
Practical Time : 9:00 AM to 1:00 PM (Tuesday) Room No. : Lab :
Introduction to Matlab--I Basics of Digital Image Processing(DIP) Introduction to Matlab--II Mathematical Preliminaries, Gear up with Matlab. Introduction to Matlab--III Computer Vision, Scope of image processing in Medical Science-I Introduction to Image Processing Tool Box--I Computer Vision, Scope of image processing in Medical Science-II Introduction to Image Processing Tool Box--II Brief discussion of the physics of PET, MRI, and ultrasound; discussion of the properties of the resulting images, and of the advantages and disadvantages of each imaging modality--I Introduction to Image Processing Tool Box--III
Mr. K. F. Rahman Dr. Saurabh Mukherjee Mr. K. F. Rahman Dr. Saurabh Mukherjee Mr. K. F. Rahman Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee
Brief discussion of the physics of PET, MRI, and ultrasound; discussion of the properties of the resulting images, and of the advantages and disadvantages of each imaging modality--II Introduction to Image Processing Tool Box--IV How to write a Research Paper (Survey, Empirical) Signal Processing using Matlab--I Illumination, Brightness and contrast, Contrast adjustment, Correlation, Convolution--I Illumination, Brightness and contrast, Contrast adjustment, Correlation, Convolution--II Signal Processing using Matlab--II
Dr. Saurabh Mukherjee
Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Mr. K. F. Rahman
Sampling theory & Quantization. Interpolation methods including nearestneighbour, linear, cubic & higher-order. Fourier (using the FFT): Continuous and Discrete. Correlation using Matlab Convolution using Matlab Wavelet Transform (Haar, various levels of Daubechies) Wavelet Transform (Haar, various levels of Daubechies)--I Implementation of spatial image transformations (rigid and non-rigid). Wavelet Transform (Haar, various levels of Daubechies)--II De-noising (convolution, FFT), deblurring (solving an ill-conditioned sparse linear system) FFT in Medical Imaging Edge detection (numerical approximation to
Mr. K. F. Rahman
42-45
Mr. K. F. Rahman
45-48 L-10 L-11 49-52
Mr. K. F. Rahman Mr. K. F. Rahman Mr. K. F. Rahman Mr. K. F. Rahman
L-12 53-56 L-13 57-60
Mr. K. F. Rahman Mr. K. F. Rahman Mr. K. F. Rahman Mr. K. F. Rahman
a partial derivative) Edge Detection in Medical Imaging Anisotropic diffusion (numerical solution of partial differential equations), superresolution. Resolution Analysis in Medical Imaging--I Discussion of intensity-based methods, including a variety of cost functions (correlation, least squares, mutual information, robust estimators) Resolution Analysis in Medical Imaging--II Optimization techniques (fixed-point iteration, gradient descent, Nelder-Mead simplex method, etc.). Search and Optimization of Tissue Detection in MI(Medical Imaging) MRI motion compensation. Early Detection of Brain Tumour using Stadwin 4.4 and MITK 3.3 Discussion of simple methods such as thresholding, region growing and watershed Thresholding implications in medical Imaging In-depth coverage on the method of snakes (adaptive mesh), level set method (numerical solution of partial differential equations) 3D construction of Cardio Images Clustering (classifiers) and its implementation. Retinal Image Analysis using MITK 3.3 Reconstruction techniques for CT (filtered back projection) and MRI (using the FFT) and its applications Coverage of the theory of the Radon transform, the Fourier transform, and how they relate to each other.
Mr. K. F. Rahman Mr. K. F. Rahman
Mr. K. F. Rahman Mr. K. F. Rahman
Mr. K. F. Rahman Mr. K. F. Rahman
SECTION--C
L-18 76-79 L-19 80-83 L-20 84-87 12-02-2013 15,16,17,18 Feb. 2013 19-02-2013 22,23,24,25 Feb. 2013 26-02-2013 1,2,3,4 March 2013 Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee
L-21 88-90 L-22 91-94
5-03-2013 08,09,11 March 2013 12-03-2012 15,16,17,18 March 2013 29,30,31 Mar. 1 April 2013 2-04-2013
Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee Dr. Saurabh Mukherjee