- LO1: To familiarize with major signal and image acquisition modalities in healthcare
- LO2: To understand instrumentation and signal characteristics associated with each modality
Course Name | Biomedical Image Processing |
Program | M. Tech. in Biomedical Instrumentation and Signal Processing ( Proposed to be RENAMED as M-Tech Biomedical Engineering & AI)* |
Semester | 1 |
Credits | 4 |
Imaging Modalities: Brief survey of major modalities for medical imaging: Ultrasound, X-ray, CT, MRI, PET, and SPECT.
Objectives of biomedical image analysis – Computer aided diagnosis, Removal of artifacts – Image Enhancement – Gray level transforms – Histogram transformation.
Spatial domain filters – Frequency domain filters – Morphological image processing – Binary morphological operations and properties – Morphological algorithms – Medical Image Segmentation, Thresholding – Region growing – Region splitting and merging – Edge detection.
Analysis of shape and texture – Representation of shapes and contours – Shape factors – Models for generation of texture – Statistical analysis of texture – Fractal analysis – Fourier domain analysis of texture – Applications – Contrast enhancement of mammograms – Detection of calcifications by region growing – Shape and texture analysis of tumours.
Reconstruction Techniques, Classification and Clustering, Examples of Image Classification for Diagnostic/Assistive Technologies, Case studies.
Image processing practical exercises:
Recommended Tools MATLAB, Python
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