@bachelorsthesis{Eckelt_2017, title = "Vascular Printing - 3D Printing of Aortic Dissections", author = "Klaus Eckelt", year = "2017", month = jan, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2017/Eckelt_2017/", } @misc{fmistelbauer-2014-adict, title = "ActiveDICOM - Enhancing Static Medical Images with Interaction", author = "Florian Mistelbauer and Gabriel Mistelbauer and Eduard Gr\"{o}ller", year = "2014", abstract = "Digital Imaging and Communications in Medicine (DICOM) is a well-establish standard in medical imaging, consisting not only of image data, but sensitive data such as patient and examination information. Nowadays, although having a large variety of advanced rendering techniques available, DICOM images are still generated and sent to the Picture Archiving and Communication System (PACS). These images are then fetched by the medical doctor from a workstation and used for medical reporting. The user has no other possibilities than being able to change the windowing function for displaying the DICOM images. If a certain region is of special interest, either images of the whole data set are generated or have to be specifically requested. Both approaches consume a considerable amount of time. Secondly, the image generation on demand remains pending until done by the responsible assistant. Despite supporting a broad range of features and being widely applied, DICOM images remain static. We propose a visualization mapping language, Active DICOM Script (ADICT), which enhances conventional DICOM with interactive elements by combining heterogeneous data, interaction and visualization. Such DICOM images are then called Active Digital Imaging and Communications in Medicine (ActiveDICOM).", month = sep, series = "EG VCBM 2014", location = "Vienna, Austria", event = "Eurographics Workshop on Visual Computing for Biology and Medicine", booktitle = "Posters at Eurographics Workshop on Visual Computing for Biology and Medicine", Conference date = "Poster presented at Eurographics Workshop on Visual Computing for Biology and Medicine (2014-09-03--2014-09-05)", URL = "https://www.cg.tuwien.ac.at/research/publications/2014/fmistelbauer-2014-adict/", } @article{Auzinger_Mistelbauer_2013_CSR, title = "Vessel Visualization using Curved Surface Reformation", author = "Thomas Auzinger and Gabriel Mistelbauer and Ivan Baclija and R\"{u}diger Schernthaner and Arnold K\"{o}chl and Michael Wimmer and Eduard Gr\"{o}ller and Stefan Bruckner", year = "2013", abstract = "Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.", month = dec, journal = "IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Scientific Visualization 2013)", volume = "19", number = "12", pages = "2858--2867", keywords = "Surface Approximation, Vessel, Reformation, Volume Rendering", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/Auzinger_Mistelbauer_2013_CSR/", } @article{mistelbauer-2013-cfa, title = "Vessel Visualization using Curvicircular Feature Aggregation", author = "Gabriel Mistelbauer and Anca Morar and Andrej Varchola and R\"{u}diger Schernthaner and Ivan Baclija and Arnold K\"{o}chl and Armin Kanitsar and Stefan Bruckner and Eduard Gr\"{o}ller", year = "2013", abstract = "Radiological investigations are common medical practice for the diagnosis of peripheral vascular diseases. Existing visualization methods such as Curved Planar Reformation (CPR) depict calcifications on vessel walls to determine if blood is still able to flow. While it is possible with conventional CPR methods to examine the whole vessel lumen by rotating around the centerline of a vessel, we propose Curvicircular Feature Aggregation (CFA), which aggregates these rotated images into a single view. By eliminating the need for rotation, vessels can be investigated by inspecting only one image. This method can be used as a guidance and visual analysis tool for treatment planning. We present applications of this technique in the medical domain and give feedback from radiologists.", month = jun, journal = "Computer Graphics Forum", volume = "32", number = "3", pages = "231--240", URL = "https://www.cg.tuwien.ac.at/research/publications/2013/mistelbauer-2013-cfa/", } @inproceedings{mistelbauer-2012-ssv, title = "Smart Super Views - A Knowledge-Assisted Interface for Medical Visualization", author = "Gabriel Mistelbauer and Hamed Bouzari and R\"{u}diger Schernthaner and Ivan Baclija and Arnold K\"{o}chl and Stefan Bruckner and Milo\v{s} \v{S}r\'{a}mek and Eduard Gr\"{o}ller", year = "2012", abstract = "Due to the ever growing volume of acquired data and information, users have to be constantly aware of the methods for their exploration and for interaction. Of these, not each might be applicable to the data at hand or might reveal the desired result. Owing to this, innovations may be used inappropriately and users may become skeptical. In this paper we propose a knowledge-assisted interface for medical visualization, which reduces the necessary effort to use new visualization methods, by providing only the most relevant ones in a smart way. Consequently, we are able to expand such a system with innovations without the users to worry about when, where, and especially how they may or should use them. We present an application of our system in the medical domain and give qualitative feedback from domain experts.", month = oct, publisher = "IEEE Computer Society", location = "Seattle, WA, USA", booktitle = "IEEE Conference on Visual Analytics Science and Technology (IEEE VAST) 2012", pages = "163--172", URL = "https://www.cg.tuwien.ac.at/research/publications/2012/mistelbauer-2012-ssv/", } @bachelorsthesis{FISCHL-2012-CTASEG, title = "Parallelized Segmentation of CT-Angiography Datasets Using CUDA", author = "Daniel Fischl", year = "2012", abstract = "Segmentation of CT-Angiography datasets is an important and difficult task. Several algorithms and approaches have already been invented and implemented to solve this problem. In this work, we present automatic algorithms for the segmentation of these CTA datasets, implemented in CUDA, and evaluate our results regarding speed and error rates. Starting with local approaches like thresholding we pro- ceed to global, object-based algorithms, like region growing and a newly developed algorithm based on dual energy CT scans (DECT), the XOR-Algorithm, presented by Karimov et al.[6] A limitation of using graphics hardware is the restricted amount of memory, which led us to use a slab-based processing approach (see section 5.3). The requirement of this work was a complete GPU implementation. But since not every task is appropriate for parallelizing, it was necessary to use iteratively parallel algorithms. This strategy though introduced speed problems that had to be analyzed and were partly solved. This work presents the principle of these GPU methods and compares them to their CPU counterparts. In the end, the quality of each algorithm is analyzed and they are compared against each other, in order to find an acceptable completely automatic segmentation algorithm for distinguishing between different types of tissues (e.g. vessels, bones, soft tissue, ...).", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2012/FISCHL-2012-CTASEG/", } @inproceedings{mistelbauer-2012-cr, title = "Centerline Reformations of Complex Vascular Structures", author = "Gabriel Mistelbauer and Andrej Varchola and Hamed Bouzari and Juraj Starinsky and Arnold K\"{o}chl and R\"{u}diger Schernthaner and Dominik Fleischmann and Eduard Gr\"{o}ller and Milo\v{s} \v{S}r\'{a}mek", year = "2012", abstract = "Visualization of vascular structures is a common and frequently performed task in the field of medical imaging. There exist well established and applicable methods such as Maximum Intensity Projection (MIP) and Curved Planar Reformation (CPR). However, when calcified vessel walls are investigated, occlusion hinders exploration of the vessel interior with MIP. In contrast, CPR offers the possibility to visualize the vessel lumen by cutting a single vessel along its centerline. Extending the idea of CPR, we propose a novel technique, called Centerline Reformation (CR), which is capable of visualizing the lumen of spatially arbitrarily oriented vessels not necessarily connected in a tree structure. In order to visually emphasize depth, overlap and occlusion, halos can optionally envelope the vessel lumen. The required vessel centerlines are obtained from volumetric data by performing a scale-space based feature extraction. We present the application of the proposed technique in a focus and context setup. Further, we demonstrate how it facilitates the investigation of dense vascular structures, particularly cervical vessels or vessel data featuring peripheral arterial occlusive diseases or pulmonary embolisms. Finally, feedback from domain experts is given.", isbn = "978-1-4673-0863-2", location = "Songdo, Korea (South) ", booktitle = "Pacific Visualization Symposium (PacificVis), 2012 IEEE", pages = "233--240", URL = "https://www.cg.tuwien.ac.at/research/publications/2012/mistelbauer-2012-cr/", } @mastersthesis{bernhard-2006-dvrcta, title = "Efficient CPU-based Direct Volume Rendering for CT-Angiography", author = "Matthias Bernhard", year = "2006", month = nov, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2006/bernhard-2006-dvrcta/", } @phdthesis{Cruz-thesis, title = "3D Modelling and Reconstruction of Peripheral Vascular Structure", author = "Alexandra La Cruz", year = "2006", abstract = "A model is a simplified representation of an object. The modeling stage could be described as shaping individual objects that are later used in the scene. For many years scientists are trying to create an appropriate model of the blood vessels. It looks quite intuitive to believe that a blood vessel can be modeled as a tubular object, and this is true, but the problems appear when you want to create an accurate model that can deal with the wide variability of shapes of diseased blood vessels. From the medical point of view it is quite important to identify, not just the center of the vessel lumen but also the center of the vessel, particularly in the presences of some anomalies, which is the case diseased blood vessels. An accurate estimation of vessel parameters is a prerequisite for automated visualization and analysis of healthy and diseased blood vessels. We believe that a model-based technique is the most suitable one for parameterizing blood vessels. The main focus of this work is to present a new strategy to parameterize diseased blood vessels of the lower extremity arteries. The first part presents an evaluation of different methods for approximating the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting using thresholds and a maximum gradient-like stop criterion, pixel-motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting have been used as shape based segmentation techniques. Since in the synthetic data set the centerline is known, an estimation of the error can be calculated in order to determine the accuracy achieved by a given method. The second part describes an estimation of the dimensions of lower extremity arteries, imaged by computed tomography. The vessel is modeled using an elliptical or cylindrical structure with specific dimensions, orientation and CT attenuation values. The model separates two homogeneous regions: Its inner side represents a region of density for vessels, and its outer side a region for background. Taking into account the point spread function of a CT scanner, which is modeled using a Gaussian kernel, in order to smooth the vessel boundary in the model. An optimization process is used to find the best model that fits with the data input. The method provides center location, diameter and orientation of the vessel as well as blood and background mean density values. The third part presents the result of a clinical evaluation of our methods, as a prerequisite step for being used in clinical environment. To perform this evaluation, twenty cases from available patient data were selected and classified as 'mildly diseased' and 'severely diseased' datasets. Manual identification was used as our reference standard. We compared the model fitting method against a standard method, which is currently used in the clinical environment. In general, the mean distance error for every method was within the inter-operator variability. However, the non-linear model fitting technique based on a cylindrical model shows always a better center approximation in most of the cases, 'mildly diseased' as well as 'severely diseased' cases. Clinically, the non-linear model fitting technique is more robust and presented a better estimation in most of the cases. Nevertheless, the radiologists and clinical experts have the last word with respect to the use of this technique in clinical environment.", month = mar, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", keywords = "Vessel Visualization, 3D Modeling, Segmentation, 3D Reconstruction", URL = "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/", }