Image Processing
Image Processing in MeVisLab Digital image processing is the use of a digital computer to process digital images through an algorithm (see Wikipedia).
MeVisLab provides multiple modules for image processing tasks, such as:
Filters Masks Transformations Arithmetics Statistics For details about Image Processing in MeVisLab, see the MeVisLab Documentation In this chapter, you will find some examples for different types of image processing in MeVisLab.
Example 1: Arithmetic operations on two images This example is also available on YouTube. Introduction We are using the Arithmetic2 module to apply basic scalar functions on two images. The module provides 2 inputs for images and 1 output image for the result.
Steps to do Develop your network Add two LocalImage modules to your workspace for the input images. Select $(DemoDataPath)/BrainMultiModal/ProbandT1.dcm and $(DemoDataPath)/BrainMultiModal/ProbandT2.dcm from MeVisLab demo data and add a SynchroView2D to your network.
Example 2: Masking images This example is also available on YouTube. Introduction The background of medical images is black for most cases. In case an image is inverted or window/level values are adapted, these black pixels outside clinical relevant pixels might become very bright or even white.
Being in a dark room using a large screen, the user might be blended by these large white regions.
Image masking is a very good way to select a defined region where image processing shall be applied.
Example 3: Region Growing This example is also available on YouTube. Introduction A very simple approach to segment parts of an image is the region growing method. A general explanation can be found here.
In this example, you will segment the brain of an image and show the segmentation results as an overlay on the original image.
Steps to do Develop your network Add a LocalImage module to your workspace and select load $(DemoDataPath)/BrainMultiModal/ProbandT1.
Example 4: Subtract 3D objects This example is also available on YouTube. Introduction In this example, we load an image and render it as WEMIsoSurface. Then we create a 3-dimensional SoSphere and subtract the sphere from the initial WEM.
Steps to do Develop your network Add a LocalImage module to your workspace and select load $(DemoDataPath)/BrainMultiModal/ProbandT1.dcm. Add a WEMIsoSurface, a SoWEMRenderer, a SoBackground and a SoExaminerViewer module and connect them as seen below.
Example 5: Clip Planes This example is also available on YouTube. Introduction In this example, we are using the SoGVRDrawOnPlane module to define the currently visible slice from a 2D view as a clip plane in 3D.
Steps to do Develop your network First we need to develop the network to scroll through the slices. Add a LocalImage module to your workspace and select the file ProbandT1 from MeVisLab demo data.
