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- Andersson, Thord, et al.
(författare)
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Modified Gradient Search for Level Set Based Image Segmentation
- 2013
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Ingår i: IEEE Transactions on Image Processing. - : IEEE Signal Processing Society. - 1057-7149 .- 1941-0042. ; 22:2, s. 621-630
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Tidskriftsartikel (refereegranskat)abstract
- Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.
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| 2. |
- Cros, Olivier, et al.
(författare)
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Micro-channels in the mastoid anatomy. Indications of a separate blood supply of the air cell system mucosa by micro-CT scanning
- 2013
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Ingår i: Hearing Research. - : Elsevier. - 0378-5955 .- 1878-5891. ; 301, s. 60-65
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Tidskriftsartikel (refereegranskat)abstract
- The mastoid air cell system has traditionally been considered to have a passive role in gas exchange and pressure regulation of the middle ear possibly with some acoustic function. However, more evidence has focused on the mucosa of the mastoid, which may play a more active role in regulation of middle ear pressure.In this study we have applied micro-CT scanning on a series of three human temporal bones. This approach greatly enhances the resolution (40–60 μm), so that we have discovered anatomical details, which has not been reported earlier. Thus, qualitative analysis using volume rendering has demonstrated notable micro-channels connecting the surface of the compact bone directly to the mastoid air cells as well as forming a network of connections between the air cells. Quantitative analysis on 2D slices was employed to determine the average diameter of these micro-channels (158 μm; range = 40–440 μm) as well as their density at a localized area (average = 75 cm−2; range = 64–97 cm−2).These channels are hypothesized to contain a separate vascular supply for the mastoid mucosa. However, future studies of the histological structure of the micro-channels are warranted to confirm the hypothesis. Studies on the mastoid mucosa and its blood supply may improve our knowledge of its physiological properties, which may have important implications for our understanding of the pressure regulation of the middle ear.
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| 5. |
- 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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| 6. |
- 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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| 8. |
- Rattfält, Linda, 1979-, et al.
(författare)
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Robust heartbeat detector based on weighted correlation and multichannel input : Implementation on the ECG recorded with textile electrodes
- 2013
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Ingår i: International Journal of E-Health and Medical Communications. - : IGI Global. - 1947-315X .- 1947-3168. ; 4:1, s. 61-71
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to develop and evaluate a robust heartbeat detector for noisy electrocardiograms (ECGs) recorded with textile electrodes. The authors suggest a method based on weighted correlation in a multi-channel ECG to obtain a heartbeat detector. Signals were acquired during rest and at movements which simulate every day activities. From each recording a segment corresponding to a heartbeat was extracted and correlated with the whole signal. From the correlation data, heartbeat candidates were derived and weighted based on their variance similarity with the heartbeat model and previous heartbeats. Finally, the outputs of each channel were added to create the global output. The output was compared to the Pan Tompkins heartbeat detector. Results are promising for recordings at rest (sensitivity = 0.97, positive predictive value (PPV) = 0.97). For static muscle tension in the torso the results were much higher than the reference method (sensitivity = 0.77, PPV = 0.85). Corresponding values for the reference method were sensitivity = 0.96 and PPV = 0.95 at rest and sensitivity = 0.52 and PPV = 0.75 during muscle tension.
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| 9. |
- Sundvall, Erik, 1973-
(författare)
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Scalability and Semantic Sustainability in Electronic Health Record Systems
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This work is a small contribution to the greater goal of making software systems used in healthcare more useful and sustainable. To come closer to that goal, health record data will need to be more computable and easier to exchange between systems.Interoperability refers to getting systems to work together and semantics concerns the study of meanings. If Semantic interoperability is achieved then information entered in one information system is usable in other systems and reusable for many purposes. Scalability refers to the extent to which a system can gracefully grow by adding more resources. Sustainability refers more to how to best use available limited resources. Both aspects are important.The main focus and aim of the thesis is to increase knowledge about how to support scalability and semantic sustainability. It reports explorations of how to apply aspects of the above to Electronic Health Record (EHR) systems, associated infrastructure, data structures, terminology systems, user interfaces and their mutual boundaries.Using terminology systems is one way to improve computability and comparability of data. Modern complex ontologies and terminology systems can contain hundreds of thousands of concepts that can have many kinds of relationships to multiple other concepts. This makes visualization challenging. Many visualization approaches designed to show the local neighbourhood of a single concept node do not scale well to larger sets of nodes. The interactive TermViz approach described in this thesis, is designed to aid users to navigate and comprehend the context of several nodes simultaneously. Two applications are presented where TermViz aids management of the boundary between EHR data structures and the terminology system SNOMED CT.The amount of available time from people skilled in health informatics is limited. Adequate methods and tools are required to develop, maintain and reuse health-IT solutions in a sustainable way. Multiple levels of modelling including a fixed reference model and another layer of flexible reusable ‘archetypes’ for domain specific data structures, is an approach with that aim used in openEHR and the ISO 13606 standard. This approach, including learning, implementing and managing it, is explored from different angles in this thesis. An architecture applying Representational State Transfer (REST) to archetype-based EHR systems, in order to address scalability, is presented. Combined with archetyping this architecture also aims at enabling a sustainable way of continuously evolving multi-vendor EHR solutions. An experimental open source implementation of it, aimed for learning and prototyping, is also presented.Manually changing database structures used for storage every time new versions of archetypes and associated data structures are needed is likely not a sustainable activity. Thus storage systems that can handle change with minimal manual interventions are desirable. Initial explorations of performance and scalability in such systems are also reportedGraphical user interfaces focused on EHR navigation, time-perspectives and highlighting of EHR content are also presented – illustrating what can be done with computable health record data and the presented approaches.Desirable aspects of semantic sustainability have been discussed, including: sustainable use of limited resources (such as available time of skilled people), and reduction of unnecessary risks. A semantic sustainability perspective should be inspired and informed by research in complex systems theory, and should also include striving to be highly aware of when and where technical debt is being built up. Semantic sustainability is a shared responsibility.The combined results presented contribute to increasing knowledge about ways to support scalability and semantic sustainability in the context of electronic health record systems. Supporting tools, architectures and approaches are additional contributions.
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