Medical Image Processing detailed syllabus for Medical Electronics (MEE) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the MEE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Medical Electronics 6th Sem scheme and its subjects, do visit MEE 6th Sem 2021 regulation scheme. The detailed syllabus of medical image processing is as follows.
Course Objectives:
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Unit I
FUNDAMENTALS OF MEDICAL IMAGE PROCESSING AND
TRANSFORMS
Overview of Image Processing system and human Visual system- Image representation – pixel and voxels, Gray scale and color models- Medical image file formats- DICOM, ANALYZE 7.5, NIFTI and INTERFILE- Discrete sampling model and Quantization- Relationship between the pixels, Arithmetic and logical operations- Image quality and Signal to Noise ratio- Image Transforms- 2D DFT, DCT, KLT. Interpret the basics of image models, Digitization of images and the transformations of medical images using Matlab.
Unit II
ENHANCEMENT TECHNIQUES
Gray level transformation- Log transformation, Power law transformation, Piecewise linear transformation. Histogram processing- Histogram equalization, Histogram Matching. Spatial domain Filtering-Smoothing filters, sharpening filters. Frequency domain filtering- Smoothing filters, Sharpening filters- Homomorphic filtering -Medical image enhancement using Hybrid filters-Performance measures for enhancement techniques. Experiment with various filtering techniques for noise reduction and enhancement in medical images using Matlab.
Unit III
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Unit IV
REGISTRATION AND VISUALISATION
Registration-Rigid body transformation, principal axes registration, and feature based. Visualisation-Orthogonal and perspective projection in medicine, Surface based rendering, Volume 94
visualization in medical image. Explain the significance of registration of various imaging modalities and appraise the concepts of image visualization in healthcare using Matlab
Unit V
APPLICATIONS OF MEDICAL IMAGE ANALYSIS
Medical Image compression- DCT and Wavelet transform based image compression, Preprocessing of medical images -Retinal images, Ultrasound -liver, kidney, Mammogram. Segmentation of ROI -blood vessels, lesions, tumour, lung nodules, feature extraction- shape and texture, Computer aided diagnosis system – performance measures (confusion matrix, ROC, AUC).
Course Outcomes:
Upon successful completion of the course, students will be able to
- Explain and apply the fundamental concepts of image processing techniques for the analysis of medical images.
- Identify and apply suitable filtering and intensity transformation techniques for given medical applications.
- Identify and segment the Region of Interest from the given medical image.
- Explore and apply current research in registration and visualization for medical image analysis.
- Explain and apply the image compression techniques.
- Design and evaluate the use of image processing fundamentals in healthcare applications, as well as their impact on health and society, and any underlying ethical issues, then communicate effectively through reflections, reports, and presentations (Target CO).
Text Books:
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Reference Books:
- Atam P.Dhawan, Medical Image Analysis, Wiley-Interscience Publication, NJ, USA 2003
- Rangaraj M. “Rangayyan, Biomedical Image Analysis”, 1st Edition, CRC Press,Published December 30, 2004.
- Joseph V.Hajnal, Derek L.G.Hill, David J Hawkes, “Medical image registration”, Biomedical Engineering series, CRC press,2001
- Milan Sonka, Image Processing, Analysis And Machine Vision, Brookes/Cole, Vikas Publishing House, 2nd edition, 1999.
- Anil Jain K, Fundamentals of Digital Image Processing, PHI Learning Pvt. Ltd., 2011.
For detailed syllabus of all other subjects of Medical Electronics, 2021 regulation curriculum do visit MEE 6th Sem subject syllabuses for 2021 regulation.
For all Medical Electronics results, visit Anna University MEE all semester results direct link.