Author :
Ritter, Felix ; Boskamp, Tobias ; Homeyer, André ; Laue, Hendrik ; Schwier, Michael ; Link, Florian ; Peitgen, Heinz-Otto
Abstract :
Since the discovery of the X-ray radiation by Wilhelm Conrad Roentgen in 1895, the field of medical imaging has developed into a huge scientific discipline. The analysis of patient data acquired by current image modalities, such as computerized tomography (CT), magnetic resonance tomography (MRT), positron emission tomography (PET), or ultrasound (US), offers previously unattained opportunities for diagnosis, therapy planning, and therapy assessment. Medical image processing is essential to leverage this increasing amount of data and to explore and present the contained information in a way suitable for the specific medical task. In this tutorial, we will approach the analysis and visualization of medical image data in an explorative manner. In particular, we will visually construct the image processing algorithms using the popular graphical data-flow builder MeVisLab, which is available as a free download for noncommercial research. We felt that it could be more interesting for the reader to see and explore examples of medical image processing that go beyond simple image enhancements. The part of exploration, to inspect medical image data and experiment with image-processing pipelines, requires software that encourages this kind of visual exploration.
Keywords :
data visualisation; image enhancement; image registration; image segmentation; medical image processing; patient diagnosis; CT; MRT; MeVisLab; PET; US; computerized tomography; graphical data flow builder; image modalities; magnetic resonance tomography; medical image analysis; medical image data analysis; medical image data visualization; medical image processing; patient data analysis; patient diagnosis; positron emission tomography; therapy assessment; therapy planning; ultrasound imaging; Algorithm design and analysis; Computed tomography; Data visualization; Image segmentation; Medical diagnostic imaging; Medical image processing; Rendering (computer graphics); X-ray imaging; Brain; Diagnostic Imaging; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Spine;