Objectives of biomedical image analysis - Computer aided diagnosis - Nature of medical images: X-ray imaging – Tomography - Nuclear medicine imaging - SPECT imaging - Positron imaging tomography – Ultrasonography - Magnetic resonance imaging. Removal of artifacts - Space domain filters - Frequency domain filters - Optimal filtering - Adaptive filters.
Image enhancement – Gray level transforms - Histogram transformation - Convolution mask operators - Contrast enhancement. Detection of regions of interest -
Thresholding and binarization - Detection of isolated lines and points - Edge detection - Region growing.
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 - Segmentation and structural analysis of texture. Pattern classification and diagnostic decision - Measures of diagnostic accuracy - Applications: Contrast enhancement of mammograms - Detection of calcifications by region growing - Shape and texture analysis of tumours.