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Maurer Michael Saffari Amir Schulter Samuel Seichter Hartmut Zeisl Bernhard Lex Alexander Arth Clemens Barakonyi István Bauer Joachim Beichel Reinhard Bischof Horst Bornik Alexander Reitinger Bernhard Bauer Christian Gruber Lukas Kainz Bernhard Pirchheim Christian Wagner Daniel Kalkofen Denis Donoser Michael Elbischger Pierre Ferstl David Fraundorfer Friedrich Reitmayr Gerhard Godec Martin Graber Gottfried Grabner Markus Grubert Jens Hartl Andreas Hauswiesner Stefan Riemenschneider Hayko Grabner Helmut Hirzer Martin Hofer Manuel Hoppe Christof Irschara Arnold Newman Joseph Junghanns Sebastian Khan Inayatullah Kalkusch Michael Karner Konrad Khlebnikov Rostislav Klaus Andreas Klopschitz Manfred Kluckner Stefan Köstinger Martin Kontschieder Peter Pirker Katrin Kruijff Ernst Langlotz Tobias Langs Georg Leberl Franz Lee Felix Leistner Christian Leitner Raimund Lenz Martin Mauthner Thomas Meixner Philipp Mendez Erick Grabner Michael Heber Markus Mühl Judith Mulloni Alessandro Ober Sandra Pacher Georg Partl Christian Pflugfelder Roman Pinz Axel Roth Peter M. Pock Thomas Puff Werner Pan Qi Ram Surinder Ranftl René Grasset Raphael Recky Michal Regenbrecht Holger Reinbacher Christian Rüther Matthias Rumpler Markus Santner Jakob Sareika Markus Schall Gerhard Schmalstieg Dieter Schulz Hans-Jörg Sormann Mario Steinberger Markus Sternig Sabine Storer Markus Straka Matthias Streit Marc Tatzgern Markus Nguyen Thanh Nguyen Thuy Trobin Werner Unger Markus Uray Martina Urschler Martin Veas Eduardo Waldner Manuela Wendel Andreas Werlberger Manuel Winter Martin Wohlhart Paul Zach Christopher Zebedin Lukas Zollmann Stefanie
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Nonlinear Registration for Intra-Modality CT Applications
(details)

Introduction

Research interests in single-modality nonlinear registration include four different kinds of subproblems. Deformable registration of two or more CT lung data sets at different states in the breathing cycle going from Functional Residual Capacity (FRC, expiration) to Total Lung Capacity (TLC, inspiration) for modelling breathing motion and deriving lung ventilation. Deformable registration of a contrast-enhanced and a native CT lung data set for deriving lung perfusion. Deformable registration of contrast-enhanced and native CT liver data sets at one or several phases in the contrast-uptake cycle for liver perfusion. And finally, highly accurate partially rigid bone registration for head and neck CT-Angiography applications to extract bone structures from CTA images.

Screenshot Deformable Lung Registration Setup

Deformable Lung Registration

The input for this task consists of native CT thorax scans at two or more different breathing states between Total Lung Capacity (TLC, inspiration) and Functional Residual Capacity (FRC, expiration). Deformable registration of distinct breathing states is a prerequisite for deriving ventilation information by simple subtraction of expiration from inspiration data or by fusion with special functional scans and it leads to models of breathing motion in the lung. For this purpose we have available high resolution sheep lung data at up to five distinct static breathing states and human lung data at inspiration/expiration. Another application of deformable lung registration is the fusion of native and contrast-enhanced CT lung data to show perfusion information again either by subtraction or by fusion with a special scan. A notion of vessel consistency should be included in the deformable registration, since it is important that the same amount of vessels is regarded before and after registration.

Deformable Liver Registration

Similar to the lung registration, liver registration for perfusion measurements is a topic of interest. Contrast-enhancing techniques are used to get up to 8 liver images at different phases of the contrast uptake cycle. Each of these images has to be registered to a native scan to correct motions due to breathing. Afterwards subtraction techniques are used to derive the amount of perfusion in the liver. The setup of the registration algorithm is very similar to the lung registration problem.

Partially Rigid Bone Registration

The intended application of rigid bone registration is a very accurate registration of bones from native and contrast-enhanced CT images of the head and the neck. In contrast-enhanced images vessels and bones have very similar intensities, such that simple segmentation algorithms like thresholding do not work which are frequently used for CTA image studies. The intended strategy for the removal of bone structures is to take a simple (threshold-based) bone segmentation taken from the native image and register it to the contrast-enhanced image. Registration is necessarysince small patient movements may occur (especially in the neck and shoulder area) between the acquisition of both kinds of images. Registration has to be very accurate in this area, since there are vessel structures that lie close to or inside the bone structures as well. It can be assumed that the bones themselves are rigid but the relative position of bones to each other may change. Pairs of bones should be registered rigidly but the relative bone movements are taken into account leading to a partially rigid registration scheme.

2004 2006

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