3D annotation and manipulation of medical anatomical structures - Vitanovski, Dime; Schaller, Christian; Hahn, Dieter; Daum, Volker; Hornegger, Joachim (Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2009)
Although the medical scanners are rapidly moving towards a three-dimensional paradigm, the manipulation and annotation/labeling of the acquired data is still performed in a standard 2D environment. Editing and annotation of three-dimensional medical structures is currently a complex task and rather time-consuming, as it is carried out in 2D projections of the original object. A major problem in 2D annotation is the depth ambiguity, which requires 3D landmarks to be identified and localized in at least two of the cutting planes. Operating directly in a three-dimensional space enables the implicit consideration of the full 3D local context, which significantly increases accuracy and speed. A three-dimensional environment is as well more natural optimizing the user's comfort and acceptance. The 3D annotation environment requires the three-dimensional manipulation device and display. By means of two novel and advanced technologies, Wii Nintendo Controller and Philips 3D WoWvx display, we define an appropriate 3D annotation tool and a suitable 3D visualization monitor. We define noncoplanar setting of four Infrared LEDs with a known and exact position, which are tracked by the Wii and from which we compute the pose of the device by applying a standard pose estimation algorithm. The novel 3D renderer developed by Philips uses either the Z-value of a 3D volume, or it computes the depth information out of a 2D image, to provide a real 3D experience without having some special glasses. Within this paper we present a new framework for manipulation and annotation of medical landmarks directly in three-dimensional volume. © 2009 SPIE.

A Gauss-Seidel Iteration Scheme for Reference-Free 3-D Histological Image Reconstruction - Gaffling, Simone; Daum, Volker; Steidl, Stefan; Maier, Andreas; Köstler, Harald; Hornegger, Joachim (IEEE Transactions on Medical Imaging, 2015)
Three-dimensional (3-D) reconstruction of histological slice sequences offers great benefits in the investigation of different morphologies. It features very high-resolution which is still unmatched by in vivo 3-D imaging modalities, and tissue staining further enhances visibility and contrast. One important step during reconstruction is the reversal of slice deformations introduced during histological slice preparation, a process also called image unwarping. Most methods use an external reference, or rely on conservative stopping criteria during the unwarping optimization to prevent straightening of naturally curved morphology. Our approach shows that the problem of unwarping is based on the superposition of low-frequency anatomy and high-frequency errors. We present an iterative scheme that transfers the ideas of the Gauss-Seidel method to image stacks to separate the anatomy from the deformation. In particular, the scheme is universally applicable without restriction to a specific unwarping method, and uses no external reference. The deformation artifacts are effectively reduced in the resulting histology volumes, while the natural curvature of the anatomy is preserved. The validity of our method is shown on synthetic data, simulated histology data using a CT data set and real histology data. In the case of the simulated histology where the ground truth was known, the mean Target Registration Error (TRE) between the unwarped and original volume could be reduced to less than 1 pixel on average after six iterations of our proposed method.
UnivIS-Import:2015-03-09:Pub.2015.tech.IMMD.IMMD5.agauss
Keywords: 3-D histology; Gauss-Seidel; reconstruction; reference-free; registration

A nonlinear projection scheme for fast rigid registration - Daum, Volker; Hahn, Dieter; Hornegger, Joachim (2007 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS-MIC, 2007)
Intensity based rigid registration algorithms commonly employed for medical image fusion are based on the iterative optimization of a pixel-by-pixel distance measure defined on the images. As medical images grow larger in size due to advanced scanner technology, evaluating such similarity measures is no longer computationally efficient. In order to overcome the inherent limitations of the standard approach we propose a new, nonlinear projection scheme that enables a very fast evaluation of the distance between two images. Current state-of-the-art projection schemes decompose a six dimensional search space into three dimensional subspaces. The proposed approach, however, yields a complete decomposition into ID subspaces. The optimization on these subspaces is highly efficient and does not require a reprojection. This scheme is therefore suitable for 2D and 3D registrations, and it is able to cope with subvolume matching problems. Furthermore, the use of modern graphics hardware allows for a highly efficient implementation. Experiments show that computation times can be reduced to less than 10 seconds with the proposed approach for 256 sized volumes. © 2007 IEEE.

Automatic Parameter Selection for Multi-Modal Image Registration - Hahn, Dieter; Daum, Volker; Hornegger, Joachim (IEEE Transactions on Medical Imaging, 2010)
Over the past ten years similarity measures based on intensity distributions have become state-of-the-art in automatic multimodal image registration. An implementation for clinical usage has to support a plurality of images. However, a generally applicable parameter configuration for the number and sizes of histogram bins, optimal Parzen-window kernel widths or background thresholds cannot be found. This explains why various research groups present partly contradictory empirical proposals for these parameters. This paper proposes a set of data-driven estimation schemes for a parameter-free implementation that eliminates major caveats of heuristic trial and error. We present the following novel approaches: a new coincidence weighting scheme to reduce the influence of background noise on the similarity measure in combination with Max-Lloyd requantization, and a tradeoff for the automatic estimation of the number of histogram bins. These methods have been integrated into a state-of-the-art rigid registration that is based on normalized mutual information and applied to CTMR, PETMR, and MRMR image pairs of the RIRE 2.0 database. We compare combinations of the proposed techniques to a standard implementation using default parameters, which can be found in the literature, and to a manual registration by a medical expert. Additionally, we analyze the effects of various histogram sizes, sampling rates, and error thresholds for the number of histogram bins. The comparison of the parameter selection techniques yields 25 approaches in total, with 114 registrations each. The number of bins has no significant influence on the proposed implementation that performs better than both the manual and the standard method in terms of acceptance rates and target registration error (TRE). The overall mean TRE is 2.34 mm compared to 2.54 mm for the manual registration and 6.48 mm for a standard implementation. Our results show a significant TRE reduction for distortion-corrected magnetic resonance images. © 2010 IEEE.
UnivIS-Import:2015-03-09:Pub.2010.tech.IMMD.IMMD5.automa

Comparison of Differences between Intra- and Inter-Ictal SPECT Images with MRI using Registration Techniques - Hahn, Dieter; Daum, Volker; Hornegger, Joachim; Kuwert, Torsten (Nuklearmedizin Kongressausgabe 02/07, 2007)

Data-Driven Density Estimation applied to SPECT Subtraction Imaging for Epilepsy Diagnosis - Hahn, Dieter; Daum, Volker; Hornegger, Joachim; Kuwert, Torsten (Proceedings of the MICCAI Workshop on Probabilistic Models For Medical Image Analysis, 2009)

Difference imaging of inter- and intra-ictal SPECT images for the localization of seizure onset in epilepsy - Hahn, Dieter; Daum, Volker; Hornegger, Joachim; Bautz, Werner; Kuwert, Torsten (2007 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS-MIC, 2007)
The comparison of inter- with intra-ictal SPECT images plays an important role during the diagnosis and treatment of epilepsy patients. Although there is already commercial software available to address this problem using complex clinical workflows, this article describes a different way of looking at this issue. During the examination various issues arise from differing tracer concentrations, patient movement between the acquisitions at different times and also the lack of morphological information. The goal of the presented work is therefore to present an approach that is on the one hand easy to use for the physician and on the other hand both reliable and robust enough to cope with the previously mentioned challenges. The proposed algorithm introduces methods that have already been applied successfully in digital subtraction angiography (DSA). The work comprises of several steps for the intensity normalization, image registration, difference imaging and the incorporation of an MR image for the spatial localization. As a result, information is provided about differences within the cerebral blood flow (CBF) and active brain areas between the intra- and inter-ictal states. Very new to the field of SPECT brain imaging is the application of non-rigid registration techniques. This helps to drastically reduce the artifacts within the difference images due to a bias of the standard rigid registration. Acquired results from a collective of 11 patients show that this additional feature helps to further improve the image quality. © 2007 IEEE.

Efficient Non-rigid Registration Algorithm Guided by Landmarks and Principle Components of a Deformation Field - Eckl, Jutta; Daum, Volker; Hornegger, Joachim; Pohl, Kilian M. (International Symposium on Biomedical Imaging, 2012)

High-Density Object Removal from Projection Images using Low-Frequency-Based Object Masking - Schwemmer, Chris; Prümmer, Marcus; Daum, Volker; Hornegger, Joachim (Bildverarbeitung für die Medizin 2010 - Algorithmen - Systeme - Anwendungen, 2010)

Landmark-constrained 3-D Histological Imaging: A Morphology-preserving Approach - Gaffling, Simone; Daum, Volker; Hornegger, Joachim (VMV 2011: Vision, Modeling & Visualization, 2011)

Non-rigid registration guided by landmarks and learning - Eckl, Jutta; Daum, Volker; Hornegger, Joachim; Pohl, Kilian M. (2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012, 2012)
Registration methods frequently rely on prior information in order to generate anatomical meaningful transformations between medical scans. In this paper, we propose a novel intensity based non-rigid registration framework, which is guided by landmarks and a regularizer based on Principle Component Analysis (PCA). Unlike existing methods in this domain, the computational complexity of our approach reduces with the number of landmarks. Furthermore, our PCA is invariant to translations. The additional regularizer is based on the outcome of this PCA. We register a skull CT scan to MR scans aquired by a MR/PET hybrid scanner. This aligned CT scan can then be used to gain an attenuation map for PET reconstruction. As a result we have a Dice coefficient for bone areas at 0.71 and a Dice coefficient for bone and soft issue areas at 0.97. © 2012 IEEE.

Non-Rigid Registration to Capture Optic Nerve Head Variability - Paulus, Jan; Bock, Rüdiger; Daum, Volker; Hornegger, Joachim (Bildverarbeitung für die Medizin 2010 - Algorithmen, Systeme, Anwendungen, 2010)

PCA Regularized Nonrigid Registration for PET/MRI Attenuation Correction - Daum, Volker; Hahn, Dieter; Hornegger, Joachim; Kuwert, Torsten (Proceedings of the MICCAI Workshop on Probabilistic Models For Medical Image Analysis, 2009)

Regression Forest-Based Organ Detection in Normalized PET Images - Fischer, Peter; Daum, Volker; Hahn, Dieter; Prümmer, Marcus; Hornegger, Joachim (Bildverarbeitung für die Medizin 2014, 2014)
The detection of organs from full-body PET images is a challenging task due to the high noise and the limited amount of anatomical information of PET imaging. The knowledge of organ locations can support many clinical applications like image registration or tumor detection. This paper is the first to propose an organ localization framework tailored on the challenges of PET. The algorithm involves intensity normalization, feature extraction and regression forests. Linear and nonlinear intensity normalization methods are compared theoretically and experimentally. From the normalized images, long-range spatial context visual features are extracted. A regression forest predicts the organ bounding boxes. Experiments show that percentile normalization is the best preprocessing method. The algorithm is evaluated on 25 clinical images with a spatial resolution of 5 mm. With 13.8mm mean absolute bounding box error, it achieves state-of-the-art results.
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.regres_5

Segmentation of kidneys using a new active shape model generation technique based on non-rigid image registration - Spiegel, Martin; Hahn, Dieter; Daum, Volker; Wasza, Jakob; Hornegger, Joachim (Computerized Medical Imaging and Graphics, 2009)
Active shape models (ASMs) are widely used for applications in the field of image segmentation. Building an ASM requires to determine point correspondences for input training data, which usually results in a set of landmarks distributed according to the statistical variations. State-of-the-art methods solve this problem by minimizing the description length of all landmarks using a parametric mapping of the target shape (e.g. a sphere). In case of models composed of multiple sub-parts or highly non-convex shapes, these techniques feature substantial drawbacks. This article proposes a novel technique for solving the crucial correspondence problem using non-rigid image registration. Unlike existing approaches the new method yields more detailed ASMs and does not require explicit or parametric formulations of the problem. Compared to other methods, the already built ASM can be updated with additional prior knowledge in a very efficient manner. For this work, a training set of 3-D kidney pairs has been manually segmented from 41 CT images of different patients and forms the basis for a clinical evaluation. The novel registration based approach is compared to an already established algorithm that uses a minimum description length (MDL) formulation. The presented results indicate that the use of non-rigid image registration to solve the point correspondence problem leads to improved ASMs and more accurate segmentation results. The sensitivity could be increased by approximately 10%. Experiments to analyze the dependency on the user initialization also show a higher sensitivity of 5-15%. The mean squared error of the segmentation results and the ground truth manually classified data could also be reduced by 20-34% with respect to varying numbers of training samples. © 2008 Elsevier Ltd. All rights reserved.

Towards Real-time Guidewire Detection and Tracking in the Field of Neuroradiology - Spiegel, Martin; Pfister, Markus; Hahn, Dieter; Daum, Volker; Hornegger, Joachim; Struffert, Tobias; Dörfler, Arnd (Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2009)
Two-dimensional roadmapping is considered state-of-the-art in guidewire navigation during endovascular interventions. This paper presents a methodology for extracting the guidewire from a sequence of 2-D roadmap images in almost real time. The detected guidewire can be used to improve its visibility on noisy fluoroscopic images or to do a back projection of the guidewire into a registered 3-D vessel tree. A lineness filter based on the Hessian matrix is used to detect only those line structures in the image that lie within the vessel tree. Loose wire fragments are properly linked by a novel connection method fulfilling clinical processing requirements. We show that Dijkstra's algorithm can be applied to efficiently compute the optimal connection path. The entire guidewire is finally approximated by a B-spline curve in a least-squares manner. The proposed method is both integrated into a commercial clinical prototype and evaluated on five different patient data sets containing up to 249 frames per image series. © 2009 SPIE.

Using a wireless motion controller for 3D medical image catheter interactions - Vitanovski, Dime; Hahn, Dieter; Daum, Volker; Hornegger, Joachim (Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2009)
State-of-the-art morphological imaging techniques usually provide high resolution 3D images with a huge number of slices. In clinical practice, however, 2D slice-based examinations are still the method of choice even for these large amounts of data. Providing intuitive interaction methods for specific 3D medical visualization applications is therefore a critical feature for clinical imaging applications. For the domain of catheter navigation and surgery planning, it is crucial to assist the physician with appropriate visualization techniques, such as 3D segmentation maps, fly-through cameras or virtual interaction approaches. There has been an ongoing development and improvement for controllers that help to interact with 3D environments in the domain of computer games. These controllers are based on both motion and infrared sensors and are typically used to detect 3D position and orientation. We have investigated how a state-of-the-art wireless motion sensor controller (Wiimote), developed by Nintendo, can be used for catheter navigation and planning purposes. By default the Wiimote controller only measure rough acceleration over a range of +/- 3g with 10% sensitivity and orientation. Therefore, a pose estimation algorithm was developed for computing accurate position and orientation in 3D space regarding 4 Infrared LEDs. Current results show that for the translation it is possible to obtain a mean error of (0.38cm, 0.41cm, 4.94cm) and for the rotation (0.16, 0.28) respectively. Within this paper we introduce a clinical prototype that allows steering of a virtual fly-through camera attached to the catheter tip by the Wii controller on basis of a segmented vessel tree. © 2009 SPIE.