| October 21st, 2020 05:05 PM | |
| prince karak | 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 |
