Dr. Julian J. Mattes Profile

Dr. Julian J. Mattes

at UMIT

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Publications (4)

Proceedings Article | 26 March 2008 Paper

3D inters-subject cardiac registration using 4D information

Alfredo Lopez, Karl Fritscher, Thomas Trieb, Rainer Schubert, Julian Mattes

Proceedings Volume 6914, 691413 (2008) https://doi.org/10.1117/12.771386

KEYWORDS: Image registration, 3D image processing, Image segmentation, 3D acquisition, Heart, Medical imaging, Astatine, Single photon emission computed tomography, Image restoration, Control systems

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In this paper we present a new approach for the registration of cardiac 4D image sequences of different subjects, where we assume that a temporal association between the sequences is given. Moreover, we allow for one (or two) selected pair(s) of associated points in time of both sequences, which we call the bridging points in time, the use of additional information such as the semi-automatic segmentation of the investigated structure. We establish the 3D inter-subject registration for all other pairs of points in time exploiting (1) the inter-subject registration for the bridging pair of points in time, (2) the intra-subject motion calculation in both sequences with respect to the bridging pair, and (3) the concatenation of the obtained transformations. We formulate a cost functional integrating the similarity measures comparing the images of the bridging pair(s) of points in time and of the current pair of points in time, respectively. We evaluated our algorithm on 8 healthy volunteers leading to 28 inter-subject combinations and we analyze the behaviour for different parameter settings weighting differently the involved pairs of points in time. The approach based on the bridging pairs outperforms a direct 3D registration of corresponding points in time, in particular in the right ventricle we gain up to 33% in registration accuracy. Starting with a cost functional taking into account the similarity at the first bridging point in time, the results improve stepwise by integrating, firstly, information from the current pair of points in time and secondly, from a second bridging point in time. Our results also show a steep rise of the importance of regularization on the registration accuracy when registering the current point in time with our procedure (17% gain in accuracy) with respect to a direct registration in the bridging point (less than 1%). However, regularization during intra-sequence registration had only minor effects on the accuracy of our registration procedure.

Proceedings Article | 10 March 2006 Paper

Quantification of the migration and deformation of abdominal aortic aneurysm stent grafts

Julian Mattes, Iris Steingruber, Michael Netzer, Karl Fritscher, Helmut Kopf, Werner Jaschke, Rainer Schubert

Proceedings Volume 6144, 61440V (2006) https://doi.org/10.1117/12.653990

KEYWORDS: Image segmentation, Image registration, Medical imaging, Image processing, Computed tomography, 3D visualizations, Arteries, Feature extraction, Blood circulation, Lithium

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Proceedings Article | 9 May 2002 Paper

Shape-adapted motion model based on thin-plate splines and point clustering for point set registration

Julian Mattes, Johannes Fieres, Roland Eils

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467194

KEYWORDS: Motion models, Annealing, 3D modeling, Image registration, Curium, Shape analysis, Optimization (mathematics), Data modeling, Prototyping, Intelligence systems

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Proceedings Article | 3 July 2001 Paper

Structural outlier detection for automatic landmark extraction

Julian Mattes, Jacques Demongeot

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431134

KEYWORDS: Image registration, Brain, Neuroimaging, Skull, Magnetic resonance imaging, Detection and tracking algorithms, Statistical modeling, Image processing, Image classification, Superposition

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