Biomedical Image processing
Biomedical signal processing involves acquiring and preprocessing physiological signals and extracting meaningful information to identify patterns and trends within the signals.
Filtering
Filters are used to remove or suppress noise in the image while preserving the detail and information of the image. Noise can be Salt & paper noise , Gaussian noise etc. Types of filters include mean filter, median filter , Gaussian Filter etc.
Functions used
imnoise()
imfilter()
imgaussfilt(A, sigma)
Segmentation
Image segmentation means partitioning the input image, by clustering pixel values of the image. It is mainly used for identifying various surfaces or living or non-living objects from an image.
Algorithms used
- Otsu thresholding
- Active contouring
- Region growing
- k-means clustering
- Gaussian mixture model
- Fuzzy c clustering