
Videos:
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- related talk: Oeltze, Steffen - Visual Analysis of Perfusion Data 


8_oeltze_4_vid1.wmv : Anatomy and myocardial perfusion of a patient suffering from 
	atherosclerosis. Upper left: Apical slice of the original perfusion data set and the 
	AHA-consistent division of the myocardium overlaid. Upper right: Apical slice of the 
	parameter volume computed for the dynamic parameter up-slope. Middle left: Bull’s-Eye 
	Plot (BEP) which color-codes the parameter up-slope. Segment 17 is missing since no slice 
	has been acquired at the apex itself. Lower left: Time-intensity curves corresponding 
	to the selected BEP segments. Lower Right: Coronary branch supplying the selected 
	segments. The user is guided through the scene by means of animations instead of being 
	confronted only with the interaction results. (Computed Tomography Coronary Angiography
	data was provided by Dr. Achenbach, Department of Radiology, University of Erlangen-
	Nürnberg, Germany and SIEMENS Medical Solutions. Magnetic Resonance Perfusion data 
	was provided by M. Fenchel, S. Miller and A. Seeger, Max Planck MR-center, University 
	of Tübingen, Germany)

8_oeltze_4_vid2.gif : Time-sequence illustrating myocardial perfusion. The injected contrast
	agent (bright regions) first arrives in the right ventricle, then travels through the
	left ventricular lumen and finally arrives in the myocardium (ring-shaped area). A 
	perfusion defect appears in the septal region (large half-moon shaped dark area, lower
        left) where no contrast agent is accumulated. (Magnetic Resonance Perfusion data was 
        provided by M. Fenchel, S. Miller and A. Seeger, Max Planck MR-center, University of 
        Tübingen, Germany)


8_oeltze_4_vid3.gif : Time-sequence illustrating cerebral perfusion. Compared to myocardial 
        perfusion (8_oeltze_4_vid2.gif), the contrast agent here leads to a decrease in 
	signal intensity in healthy tissue. This is due to the applied T2-weighted imaging 
        (in contrast to T1-weighted imaging). The infarction zone remains bright and is
        located within the right hemisphere which appears left in the image. (Magnetic 
        Resonance Perfusion data was provided by J. Wiener, Radiology, Boca Raton Community 
        Hospital, Floria, US) 

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- related talk: Preim, Bernhard - 3D Visualization of Vascular Structures


8_preim_5_vid1.avi : Portal vein inside a human liver together with a tumor (lower left). 
        Comparison of the visualization of vasculature by means of isosurface rendering 
        (upper left), the concatenation of truncated cones along the vessel skeleton (upper 
        right) and Convolution Surfaces (lower right). The latter two methods are model-based 
        approaches which visualize vasculature based on the corresponding vessel skeleton and 
        associated radius information. In close-up views, the isosurface rendering exhibits 
        nasty stair case artifacts while the truncated cone approach shows creases and shading 
        discontinuities at branchings. However, the Convolution surface appears smooth and 
        organic even at branchings. (Image analysis results were provided by Milo Hindennach, 
        MeVis Research Center, Bremen, Germany)  
  

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- related talk: Zachow, Stefan - Simulation and Visualization for Surgical Planning


8_zachow_2_vid1.mpg : The animation shows an example for 3D segmentation of
                medical image data using a statistical shape model of a liver.
                Such a model captures the most characteristic shape variations
                derived from some training set using statistical methods.
                The mean shape model is initialized inside the bounding box
                of the image stack. In a first step the mean model is
                rigidly transformed. Afterwards the statistical shape modes are
                iteratively optimized based on an analysis of intensity profiles
                at the boundary of the liver (image forces).

8_zachow_2_vid2.mpg : This movie shows an automatic 3D segmentation of the liver
                in a contrast enhanced CT data set. The segmentation process is
                depicted via the intersection of a statistical 3D liver model
                and an arbitrarily selected coronal slice. The yellow lines show
                the contours of a manual segmentation. The red line shows the
                automatic segmentation process. The blue line demonstrates where
                the statistical shape model based segmentation reaches its optimum,
                due to the restricted flexibility. In a final free form segmentation
                step the shape model's boundaries are attracted to the image
                contours (also in red).

8_zachow_2_vid3.mpg : Gives an overview on computer assisted maxillofacial
                surgery planning (with audio). A bimaxillary osteotomy of the
                jaws with combined relocation of the mobilized bone parts is
                demonstrated. The new arrangement of facial tissue is simulated
                with finite-element methods on a tetrahedral grid of the virtual
                patient's soft tissue.

8_zachow_2_vid4.mpg : demonstrates the interactive planning of bone cuts on
                virtual patient models.

8_zachow_2_vid5.mpg : demonstrates a planning of a bimaxillary osteotomy for
                maxillofacial surgery on basis of a planning model, reconstructed
                from CT data. The maxilla and the mandibular corpus are mobilized
                with bone cuts (so called osteotomies). Afterwards the maxilla is
                advanced and the mandible is set back to achieve dental occlusion.

8_zachow_2_vid6.mpg : shows the soft tissue prediction according to the bone
                relocation of the patient in the previous video. The effects of
                the bone relocation on the facial soft tissue is simulated and
                visualized for the assessment of the esthetic rehabilitation. 

8_zachow_2_vid7.mpg : shows a visualization of nasal inflow (inhalation)
                with color coded particles (velocity) based on a CFD simulation

8_zachow_2_vid8.mpg : shows a visualization of nasal outflow (exhalation)
                with color coded particles (velocity) based on a CFD simulation
 
8_zachow_2_vid9.mpg : shows the motion of particles that have been released at
                the nostrils of the nose model during simulated inhalation.
                Left and right nostril sides are colored differently.                
    
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