Bildverarbeitung für die Medizin 2014: Algorithmen - Systeme by Thomas Martin Deserno, Heinz Handels, Hans-Peter Meinzer,

By Thomas Martin Deserno, Heinz Handels, Hans-Peter Meinzer, Thomas Tolxdorff

In den letzten Jahren hat sich der Workshop "Bildverarbeitung für die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2014 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespräche zwischen Wissenschaftlern, Industrie und Anwendern. Die Beiträge dieses Bandes - einige davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung und -akquisition, Molekulare Bildgebung, Visualisierung und Animation, Bildsegmentierung und -fusion, Anatomische Atlanten, Zeitreihenanalysen, Biomechanische Modellierung, Klinische Anwendung computerunterstützter Systeme, Validierung und Qualitätssicherung u.v.m.

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Extra info for Bildverarbeitung für die Medizin 2014: Algorithmen - Systeme - Anwendungen Proceedings des Workshops vom 16. bis 18. März 2014 in Aachen

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The ability to switch from a map to a satellite view has been adapted to allow users to switch from one stain to Ă ď Đ Fig. 1. Screenshot from the graphical user interface of the prototype: (a) main view with full-screen presentation of a virtual tissue slide. (b) Multiview panel with coregistered views of other stains. The box frame in the center of the main view indicates the portion of the image shown for each available stain. (c) Thumbnail overview shows the section on display in the main view (green box frame) and allows for fast navigation.

The reduction allows us to fit the parameters on a uniform set of initial values covering all physically meaningful ones. The best fit then is the one with the smallest residual error. This eliminates the need for a patient dependent initialization, which is a significant drawback of existing algorithms. Due to the larger dimension, this approach is computationally infeasible in the original four dimensional search space. 4 Discussion We have proposed a novel optimization method to estimate the GFR from the separable compartment model.

2) consists of the determination of the pleural contours, the detection of the thickening’s tissue, and the volumetry of the detected thickenings. A full automatic registration of two consecutive CT data carries out the matching of the same thickenings to fulfill the change follow-up, while doctors still have the possibility to supervise the assessment results. Fig. 2. Schematic workflow of the new implemented automated assessment system for pleural thickenings with consecutive CT data as input and the follow-up assessment report as output.

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