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Advanced Biomedical Image Processing: Course Outline (BM-538)

Biomedical image processing is a very broad field; it covers biomedical signal gathering, image forming, picture processing, and image display to medical diagnosis based on features extracted from images

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Course Contents

Introduction, Digital Image, pixel, Digital Image Processing and its applications, medical images, Digital Image Fundamentals, Sampling and quantization, Aliasing and moiré patterns, bits per pixel & shades, spatial resolution & image size, Zooming & shrinking images, Introduction to MATLAB and image processing toolbox, Relationship between pixels, Neighbors of a pixel, Adjacency, connectivity, region & boundaries, distance measures, Introduction to brightness and contrast, Basic Gray Level transformations, Image Negative, Log transform, Gamma correction, Piecewise linear transformations, Contrast stretching and thresholding, Intensity-level slicing, Bitplane slicing, Histogram Processing, Introduction to image Histogram , Histogram sliding, Histogram stretching, Histogram equalization, Enhancement using arithmetic/logic operations, Spatial Filtering: Introduction to noise and its types, smoothing spatial filters (Mean and Median filters), sharpening spatial filters (Laplace and Sobel), un-sharp masking and high-boost filtering, Combining Spatial Enhancement methods, Frequency Domain Filtering:  Review of Fourier transform and convolution theorem, 2D-FT, FT and frequency components of an image, introduction to Lowpass and highpass filtering, Lowpass and Highpass Filters:  Ideal filters, Butterworth filters, Gaussian filters. Filters comparison, Unsharp Masking, High-Boost Filtering, Morphological Image Processing, Dilation and erosion, Opening and closing, Hit or miss transformation, Basic morphological algorithms, Extension to grayscale images, Image Segmentation: What is segmentation, Detection of discontinuities, Edge linking and boundary detection, Segmentation by thresholding, Region based segmentation, Segmentation by morphological watershed, Introduction to object recognition, classification and image compression, Advance topics in Image Processing

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