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Old October 21st, 2020, 05:05 PM
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Default Sathyabama Institute of Science and Technology B.Tech - BioMedical Engineering SBMA1603 Medical Image Processing Syllabus

Sathyabama Institute of Science and Technology B.Tech - BioMedical Engineering SBMA1603 Medical Image Processing Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY


SBMA1603 MEDICAL IMAGE PROCESSING
L T P Credits Total Marks
3 0 0 3 100

UNIT 1 IMAGE FUNDAMENTALS 9 Hrs.
Introduction - Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and
Acquisition – Image Sampling and Quantization –Zooming and Shrinking of digital images - Relationships between pixels -
color models

UNIT 2 IMAGE ENHANCEMENT 9 Hrs.
Enhancement by point processing - Gray level transformations - Histogram processing - Image subtraction - Image
averaging. Basics of Spatial Filtering - Smoothing and Sharpening Spatial Filtering, Enhancements in Frequency Domain -
low pass filtering - High pass filtering. 2D DFT and their properties.

UNIT 3 IMAGE RESTORATION 9 Hrs.
Model Image Restoration - degradation model, Noise models – Mean Filters – Order Statistics – Adaptive filters – Band
reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering

UNIT 4 IMAGE SEGMENTATION 9 Hrs.
Edge and Line Detection, Edge linking via Hough transform – Thresholding - Region based segmentation – Region growing
– Region splitting and merging – Morphological processing- erosion and dilation, Segmentation by morphological
watersheds – basic concepts – Dam construction – Watershed segmentation algorithm.

UNIT 5 IMAGE COMPRESSION AND RECOGNITION 9 Hrs.
Fundamentals, Image compression models, Huffman, Run Length Encoding, Arithmetic coding, Lossless Predictive Coding
and Lossy Predictive Coding, Boundary representation, Boundary descriptors - Fourier Descriptor, Regional Descriptors –
Topological feature, Texture, Patterns and Pattern classes - Recognition based on matching.
Max. 45 Hrs.

COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - Understands the fundamental concepts of digital image processing
CO2 - Demonstrates the suitable technique for accomplishing image preprocessing task
CO3 - Explains the restoration process and filtering techniques
CO4 - Illustrate the steps involved in segmentation process
CO5 - Analyze the performance of image compression and recognition methods
CO6 - Assess the impact of digital image processing for medical application

TEXT / REFERENCE BOOKS
1. Rafael C. Gonzales, Richard E. Woods, “Digital Image Processing”, 3rd Edition, Pearson Education, 2010.
2. Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, “Digital Image Processing Using Matlab”, 3rd Edition Tata
McGraw Hill Pvt. Ltd., 2011.
3. Anil Jain K. “Fundamentals of Digital Image Processing”, PHI Learning Pvt. Ltd., 2011.
4. William K. Pratt, “Introduction to Digital Image Processing”, CRC Press, 2013.
5. Chris Solomon, Toby Breckon, “Fundamentals of Digital Image Processing – A practical approach with examples in
Matlab”, Wiley-Blackwell, 2010.
6. Jayaraman, “Digital Image Processing”, Tata McGraw Hill Education, 2011.
7. Malay K. Pakhira, “Digital Image Processing and Pattern Recognition”, 1st Edition, PHI Learning Pvt. Ltd., 2011.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN
Max Marks: 100 Exam Duration: 3 Hrs
PART A: 10 Questions of 2 marks each - No choice 20 Marks
PART B: 2 Questions from each unit of internal choice; each carrying 16 marks 80 Marks
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