| 11. |
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| 12. |
- Karlsson, Anette, et al.
(författare)
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Automatic and Quantitative Assessment of Total and Regional Muscle Tissue Volume using Multi-Atlas Segmentation
- 2014
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Accurate and precise assessment of human muscle tissue is important for further understanding of different muscle diseases and syndromes. We present a rapid whole body MR method for automatic quantification of total and regional muscle volume. The method is based on multi-atlas segmentation of intensity corrected water-fat separated images. The method was validated with a leave-one-out approach, using manually segmented atlases from 10 subjects as ground truth. The result gave a coefficient of variation on total muscle volume equal to 1.25±1.35 % (mean ± standard deviation). The method enables cost-efficient large-scale studies, investigating conditions such as sarcopenia and muscular dystrophies.
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| 13. |
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| 14. |
- Lidell, Martin, 1970, et al.
(författare)
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Evidence for two types of brown adipose tissue in humans
- 2013
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 19:5, s. 631-634
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Tidskriftsartikel (refereegranskat)abstract
- The previously observed supraclavicular depot of brown adipose tissue (BAT) in adult humans was
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| 15. |
- Läthén, Gunnar, et al.
(författare)
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Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel Visualization
- 2012
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Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : IEEE. - 1077-2626 .- 1941-0506. ; 18:12, s. 2345-2354
-
Tidskriftsartikel (refereegranskat)abstract
- Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization- based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration.
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| 16. |
- Läthén, Gunnar, et al.
(författare)
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Blood vessel segmentation using multi-scale quadrature filtering
- 2010
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Ingår i: Pattern Recognition Letters. - : Elsevier. - 0167-8655 .- 1872-7344. ; 31:8, s. 762-767
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Tidskriftsartikel (refereegranskat)abstract
- The segmentation of blood vessels is a common problem in medical imagingand various applications are found in diagnostics, surgical planning, trainingand more. Among many dierent techniques, the use of multiple scales andline detectors is a popular approach. However, the typical line lters usedare sensitive to intensity variations and do not target the detection of vesselwalls explicitly. In this article, we combine both line and edge detection usingquadrature lters across multiple scales. The lter result gives well denedvessels as linear structures, while distinct edges facilitate a robust segmentation.We apply the lter output to energy optimization techniques for segmentationand show promising results in 2D and 3D to illustrate the behavior of ourmethod. The conference version of this article received the best paper award inthe bioinformatics and biomedical applications track at ICPR 2008.
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| 17. |
- Läthén, Gunnar, 1981-, et al.
(författare)
-
Evaluation of transfer function methods in direct volume rendering of the blood vessel lumen
- 2014
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Ingår i: Proceedings from the EG VCBM 2014. Eurographics Workshop on Visual Computing for Biology and Medicine, Vienna, Austria, September 4–5, 2014. - : Eurographics - European Association for Computer Graphics. - 9783905674620 ; , s. 117-126
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Konferensbidrag (refereegranskat)abstract
- Visualization of contrast enhanced blood vessels in CT angiography data presents a challenge due to varying concentration of the contrast agent. The purpose of this work is to evaluate the correctness (effectiveness) in visualizing the vessel lumen using two different 3D visualization strategies, thereby assessing the feasibility of using such visualizations for diagnostic decisions. We compare a standard visualization approach with a recent method which locally adapts to the contrast agent concentration. Both methods are evaluated in a parallel setting where the participant is instructed to produce a complete visualization of the vessel lumen, including both large and small vessels, in cases of calcified vessels in the legs. The resulting visualizations are thereafter compared in a slice viewer to assess the correctness of the visualized lumen. The results indicate that the participants generally overestimated the size of the vessel lumen using the standard visualization, whereas the locally adaptive method better conveyed the true anatomy. The participants did find the interpretation of the locally adaptive method to be less intuitive, but also noted that this did not introduce any prohibitive complexity in the work flow. The observed trends indicate that the visualized lumen strongly depends on the width and placement of the applied transfer function and that this dependency is inherently local rather than global. We conclude that methods that permit local adjustments, such as the method investigated in this study, can be beneficial to certain types of visualizations of large vascular trees
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| 18. |
- Läthén, Gunnar, 1981-
(författare)
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Level Set Segmentation and Volume Visualization of Vascular Trees
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Medical imaging is an important part of the clinical workflow. With the increasing amount and complexity of image data comes the need for automatic (or semi-automatic) analysis methods which aid the physician in the exploration of the data. One specific imaging technique is angiography, in which the blood vessels are imaged using an injected contrast agent which increases the contrast between blood and surrounding tissue. In these images, the blood vessels can be viewed as tubular structures with varying diameters. Deviations from this structure are signs of disease, such as stenoses introducing reduced blood flow, or aneurysms with a risk of rupture. This thesis focuses on segmentation and visualization of blood vessels, consituting the vascular tree, in angiography images.Segmentation is the problem of partitioning an image into separate regions. There is no general segmentation method which achieves good results for all possible applications. Instead, algorithms use prior knowledge and data models adapted to the problem at hand for good performance. We study blood vessel segmentation based on a two-step approach. First, we model the vessels as a collection of linear structures which are detected using multi-scale filtering techniques. Second, we develop machine-learning based level set segmentation methods to separate the vessels from the background, based on the output of the filtering.In many applications the three-dimensional structure of the vascular tree has to be presented to a radiologist or a member of the medical staff. For this, a visualization technique such as direct volume rendering is often used. In the case of computed tomography angiography one has to take into account that the image depends on both the geometrical structure of the vascular tree and the varying concentration of the injected contrast agent. The visualization should have an easy to understand interpretation for the user, to make diagnostical interpretations reliable. The mapping from the image data to the visualization should therefore closely follow routines that are commonly used by the radiologist. We developed an automatic method which adapts the visualization locally to the contrast agent, revealing a larger portion of the vascular tree while minimizing the manual intervention required from the radiologist. The effectiveness of this method is evaluated in a user study involving radiologists as domain experts.
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| 19. |
- Läthén, Gunnar, et al.
(författare)
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Non-ring Filters for Robust Detection of Linear Structures
- 2010
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Ingår i: Proceedings of the 20th International Conference on Pattern Recognition. - Los Alamitos, CA, USA : IEEE Computer Society. - 9781424475421 ; , s. 233-236
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Konferensbidrag (refereegranskat)abstract
- Many applications in image analysis include the problem of linear structure detection, e.g. segmentation of blood vessels in medical images, roads in satellite images, etc. A simple and efficient solution is to apply linear filters tuned to the structures of interest and extract line and edge positions from the filter output. However, if the filter is not carefully designed, artifacts such as ringing can distort the results and hinder a robust detection. In this paper, we study the ringing effects using a common Gabor filter for linear structure detection, and suggest a method for generating non-ring filters in 2D and 3D. The benefits of the non-ring design are motivated by results on both synthetic and natural images.
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| 20. |
- Moreno, Rodrigo, 1973-, et al.
(författare)
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Correlations between fabric tensors computed on cone beam and microcomputed tomography images
- 2014
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Ingår i: Computational Vision and Medical Image Processing IV. - : CRC Press. - 9781138000810 ; , s. 393-398
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Konferensbidrag (refereegranskat)abstract
- Computational Vision and Medical Image Processing. VIPIMAGE 2013contains invited lectures and full papers presented at VIPIMAGE 2013 - IV ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (Funchal, Madeira Island, Portugal, 14-16 October 2013). International contributions from 16 countries provide a comprehensive coverage of the current state-of-the-art in the fields of: 3D Vision; Computational Bioimaging and Visualization; Computational Vision and Image Processing applied to Dental Medicine; Computational Vision; Computer Aided Diagnosis, Surgery, Therapy, and Treatment; Data Interpolation, Registration, Acquisition and Compression; Image Processing and Analysis; Image Segmentation; Imaging of Biological Flows; Medical Imaging; Physics of Medical Imaging; Shape Reconstruction; Signal Processing; Simulation and Modeling; Software Development for Image Processing and Analysis; Telemedicine Systems and their Applications; Trabecular Bone Characterization; Tracking and Analysis of Movement; Virtual Reality.Related techniques covered in this book include the level set method, finite element method, modal analyses, stochastic methods, principal and independent components analysis and distribution models. Computational Vision and Medical Image Processing. VIPIMAGE 2013 is useful to academics, researchers and professionals in Biomechanics, Biomedical Engineering, Computational Vision (image processing and analysis), Computer Sciences, Computational Mechanics and Medicine.
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