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Werner R.,University of Hamburg | Ehrhardt J.,University of Hamburg | Schmidt-Richberg A.,University of Hamburg | Hei A.,Westcoast University of Applied science | Handels H.,University of Hamburg
International Journal of Computer Assisted Radiology and Surgery | Year: 2010

Purpose: Motivated by radiotherapy of lung cancer non- linear registration is applied to estimate 3D motion fields for local lung motion analysis in thoracic 4D CT images. Reliability of analysis results depends on the registration accuracy. Therefore, our study consists of two parts: optimization and evaluation of a non-linear registration scheme for motion field estimation, followed by a registration-based analysis of lung motion patterns. Methods: The study is based on 4D CT data of 17 patients. Different distance measures and force terms for thoracic CT registration are implemented and compared: sum of squared differences versus a force term related to Thirion's demons registration; masked versus unmasked force computation. The most accurate approach is applied to local lung motion analysis. Results: Masked Thirion forces outperform the other force terms. The mean target registration error is 1.3 ± 0.2 mm, which is in the order of voxel size. Based on resulting motion fields and inter-patient normalization of inner lung coordinates and breathing depths a non-linear dependency between inner lung position and corresponding strength of motion is identified. The dependency is observed for all patients without or with only small tumors. Conclusions: Quantitative evaluation of the estimated motion fields indicates high spatial registration accuracy. It allows for reliable registration-based local lung motion analysis. The large amount of information encoded in the motion fields makes it possible to draw detailed conclusions, e.g., to identify the dependency of inner lung localization and motion. Our examinations illustrate the potential of registration-based motion analysis. © 2010 CARS.


Edeler T.,Westcoast University of Applied science | Ohliger K.,Westcoast University of Applied science | Hussmann S.,Westcoast University of Applied science | Mertins A.,University of Lubeck
IEEE Transactions on Instrumentation and Measurement | Year: 2012

In this paper, we present a new compressed-sensing (CS) setup together with a new scalable CS model, which allows the tradeoff between system complexity (number of detectors) and time (number of measurements). We describe the calibration of the system with respect to model parameters and show the reconstruction of compressed measurements according to the new model, which are acquired with the proposed setup. The proposed model and its parameter are evaluated with the established measures, i.e., restricted isometry property and coherence. The resulting consequences for usable sparsifying basis are derived on this evaluation. With the proposed setup, it is possible to acquire high-resolution images with a low-resolution camera. © 2012 IEEE.


Edeler T.,Westcoast University of Applied science | Ohliger K.,Westcoast University of Applied science | Hussmann S.,Westcoast University of Applied science | Mertins A.,University of Lubeck
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2011

In this paper we present a new compressed sensing model and reconstruction method for multi-detector signal acquisition. We extend the concept of the famous single-pixel camera to a multi-detector device with the benefit of reducing measurement time, while still providing resolution enhancement and deblurring. We provide a scalable model which allows the trade off between system complexity (number of detectors) and time (number of measurements). © 2011 IEEE.


Edeler T.,Westcoast University of Applied science | Ohliger K.,Westcoast University of Applied science | Hussmann S.,Westcoast University of Applied science | Mertins A.,University of Lubeck
International Conference on Signal Processing Proceedings, ICSP | Year: 2010

In this paper, we propose a novel way of using time-of-flight camera depth and amplitude images to reduce the noise in depth images with prior knowledge of spatial noise distribution, which is correlated with the incident light falling on each pixel. The denoising is done in wavelet space and the influence and implications of the extended noise model to wavelet space and common denoising methods are shown. © 2010 IEEE.


Edeler T.,Westcoast University of Applied science | Arbeiter M.,Westcoast University of Applied science | Ohliger K.,Westcoast University of Applied science | Hussmann S.,Westcoast University of Applied science | Mertins A.,University of Lubeck
International Conference on Signal Processing Proceedings, ICSP | Year: 2010

In this paper we propose a novel way of estimating the rotation angle (shifts between consecutive scan lines) of bar codes in 2D images. The proposed method is compared to a well-established method, and results with real and simulated image data are presented. © 2010 IEEE.

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