Biomedical Image Processing

Course: Biomedical Image Processing

Code: 3ФЕИТ05024

ECTS points: 6 ECTS

Number of classes per week: 3+0+0+3

Lecturer: Prof. Dr. Lidija Ololoska - Gagoska

Course Goals (acquired competencies): Having successfully completed this course, you will be able to: explain the fundamentals of: image formation and acquisition, image representation in the spatial and frequency domains, the respective roles of sampling, quantization, transformation and the HVS; explain the basic mechanisms and modalities of biomedical imaging; understand the characteristics of images obtained via different mechanisms and modalities; roughly understand the applicability of individual modalities to medical diagnostics/therapy; demonstrate practical basic image processing skills ( ltering, enhancement, restoration, motion, compression, segmentation, registration); discuss applications of image processing techniques to biomedical image processing and choose what types kinds of image processing are suitable for given biomedical applications; evaluate whether an image processing system is a good candidate for given biomedical information system; keep up with recent advances in image processing and identify possible biomedical applications.

Course Syllabus: Basic concepts in digital image processing: Image representation in the spatial and frequency domains; Digitization; Visual perception; Noise and image quality; Components of an image processing system.  Biomedical imaging modalities: physics of X-rays, the Fourier slice theorem, x-ray and CAT imaging; Physical and physiological principles of magnetic resonance and MR imaging; Physical and physiological principles of ultrasound and ultrasound imaging.  Basics of morphological image processing: Introduction; Logic operations on digital images; Dilation and erosion; Openning and closing.  Filtering, enhancement and restoration: Intensity modi cations; Mask processing; Spatial frequency processing; Wavelet denoising.  Motion: Introduction; Motion quanti cation from image sequences; Application for measuring dynamic biological phenomena.  Basics of image compression: Introduction; Lossless compression; Lossy compression. Edge detection and image segmentation: Edge detection; Thresholding; Region-based segmentation; Segmentation by morphological watersheds; Application of motion for segmentation.  Rigid and non-rigid image registration: Introduction and transformations; Match metrices; Optimization and interpolation; Robustness.

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