Medical Imaging Software + Help

Download the Virtual Lab GUIs and documentation

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Medical Imaging Software only

Download only the VLab GUIs

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Medical Imaging Virtual Lab

Under "Medical Imaging" Virtual Lab, interactive exercises through Graphical User Interfaces (GUIs) are implemented. The students are able to study the following topics:

  1. Image equalization
  2. Image denoising
  3. Image registration
  4. Image Fusion
  • Download the Matlab software and documentation here (14MB, .rar)
  • Download only the Matlab software here (4MB, .rar)

Image equalization

The problem definition for "image equalization" is very simple: Some pictures have poor contrast. Namely, the distribution of image brightness values, i.e. its histogram, is very non-uniform. Image contrast enhancement techniques aim at recovering some of the apparently lost contrast in an image by remapping the brightness values, in such a way that they become more evenly distributed.

 

Using the “Image equalization” Graphical User Interface (GUI) one could study the idea of image equalization and two standard image equalization algorithms:

  1. Histogram Equalization,
  2. Contrast-Limited Adaptive Histogram Equalization (CLAHE).

One can open any source image file, select the equalization algorithm, specify its parameters and apply equalization to the input image.

  • Download the Matlab GUI here (0.3MB, .rar)

Image denoising

“Image denoising” refers to the process of recovering a digital image that has been contaminated by some type(s) of noise. Images taken either by digital cameras or by conventional film cameras pick up noise from a variety of sources. The use of these images requires that the noise will be (partially) removed, either for aesthetic purposes or for practical purposes such as in computer vision applications

The “Image Denoising” Graphical User Interface (GUI) helps the user to study the various types of noise, understand the idea of image denoising and study various denoising algorithms:

  1. Application of low-pass filters,
  2. Wavelet Transform (WT)-based denoising,
  3. Controurlet Transform (CoT)-based denoising,
  4. Independent Component Analysis (ICA)-based denoising.

 

  • Download the Matlab GUI here (1MB, .rar)

Image registration

“Image registration” is the process of overlaying two or more images of the same scene taken at the same or different times, from different viewpoints, and/or by different sensors.

With the use of the “Image Registration” Graphical User Interface (GUI) the user is able to study the notion of “image registration” and work with three different registration algorithms:

  1. The first one is based on the manual selection of feature control points.
  2. The second one works in the spatial frequency domain.
  3. The third one is based on automatic feature points estimation.

 

  • Download the Matlab GUI here (1.5MB, .rar)

Image Fusion

“Image fusion” refers to the process of combining relevant information from two or more images of the same scene into a single image, enhancing the perception of the scene. The resulting image is more informative than any of the input images.

With the use of two different Graphical User Interfaces (GUIs) the user can study the main ideas in “image fusion” and work with many different fusion algorithms:

  1. Four (4) simple fusion algorithms,
  2. Eight (8) pyramidal decomposition-based algorithms,
  3. Independed Component Analysis (ICA) - based algorithms.
  • Download the Matlab GUIs here (1MB, .rar)

 

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