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Proceedings. 22nd International Conferenceon Pattern Recognition ICPR 2014, 24-28 August 2014, Stockholm, Sweden
- 2014
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Proceedings (redaktörskap) (refereegranskat)abstract
- On behalf of the Organizing Committee, it is my honor and privilege to present the scientific program of the 22nd International Conference on Pattern Recognition. ICPR 2014 is hosted by the Swedish Society for Automated Image Analysis (SSBA) and supported by the universities of Linkoping, Lund and Uppsala.ICPR 2014 has five scientific tracks: Computer Vision; Pattern Recognition and Machine Learning; Image, Speech, Signal and Video Processing; Document Analysis, Biometrics and Pattern Recognition Applications; and Biomedical Image Analysis. For each track there is an Invited Speaker who will share their deep knowledge and experience with us. The perhaps most apparent novelty in this ICPR is the change from four to six paged papers, which is significantly more than a 50% increase in the actual content, disregarding the title, abstract and reference list. Our hope and belief is that this has improved the possibility for the reviewers to make well-justified evaluations of the manuscripts, and also improved the readability of the final papers and, as a consequence, improved the general quality of the accepted papers.The organization of ICPR 2014 would not have been possible without the generous contributions by our major partners, The City of Stockholm, SSBA, eSSENCE and SeRC. Also the financial contributions of our other partners and exhibitors as well as the technical co-sponsorship by IEEE Computer Society are gratefully acknowledged, and so is the support and advices from IAPR and the ICPR Liaison Committee. I also want to express my sincere gratitude to the Program and Publication Chairs, the Track Chairs, Area Chairs and all reviewers for their great efforts in putting this scientific program together. And, perhaps most of all, I want to thank all the contributing authors who filled it with contents of highest scientific quality. Finally, I would like to express my gratitude to all attendees. Without your presence, there simply wouldn't be any conference.
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| 133. |
- 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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| 134. |
- Rehn, Martin, 1975-
(författare)
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Some computational aspects of attractor memory
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis I present novel mechanisms for certain computational capabilities of the cerebral cortex, building on the established notion of attractor memory. A sparse binary coding network for generating efficient representation of sensory input is presented. It is demonstrated that this network model well reproduces receptive field shapes seen in primary visual cortex and that its representations are efficient with respect to storage in associative memory. I show how an autoassociative memory, augmented with dynamical synapses, can function as a general sequence learning network. I demonstrate how an abstract attractor memory system may be realized on the microcircuit level -- and how it may be analyzed using similar tools as used experimentally. I demonstrate some predictions from the hypothesis that the macroscopic connectivity of the cortex is optimized for attractor memory function. I also discuss methodological aspects of modelling in computational neuroscience.
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| 135. |
- Ridderstolpe, Lisa, et al.
(författare)
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Canonical correlation analysis of risk factors and clinical outcomes in cardiac surgery
- 2005
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Ingår i: Journal of medical systems. - : Springer. - 0148-5598 .- 1573-689X. ; 29:4, s. 357-377
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Tidskriftsartikel (refereegranskat)abstract
- Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.
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| 136. |
- Rodríguez-Vila, Borja, et al.
(författare)
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3D deformable registration for monitoring radiotherapy treatment in prostate cancer
- 2007
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Ingår i: Image Analysis. - Berlin/Heidelberg, Germany : Springer Berlin/Heidelberg. - 9783540730392 - 3540730400 - 9783540730408 ; , s. 750-759
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Konferensbidrag (refereegranskat)abstract
- Two deformable registration methods, the Demons and the Morphon algorithms, have been used for registration of CT datasets to evaluate their usability in radiotherapy planning for prostate cancer. These methods were chosen because they can perform deformable registration in a fully automated way. The experiments show that for intrapatient registration both of the methods give useful results, although some differences exist in the way they deform the template. The Morphon method has, however, some advantageous compared to the Demons method. It is invariant to the image intensity and it does not distort the deformed data. The conclusion is therefore to recommend the Morphon method as a registration tool for this application. A more flexible regularization model is needed, though, in order to be able to catch the full range of deformations required to match the datasets.
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| 137. |
- Romu, Thobias, et al.
(författare)
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A randomized trial of cold-exposure on energy expenditure and supraclavicular brown adipose tissue volume in humans
- 2016
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Ingår i: Metabolism-Clinical and Experimental. - : Elsevier BV. - 0026-0495 .- 1532-8600. ; 65:6, s. 926-934
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Tidskriftsartikel (refereegranskat)abstract
- Objective. To study if repeated cold-exposure increases metabolic rate and/or brown adipose tissue (BAT) volume in humans when compared with avoiding to freeze. Design. Randomized, open, parallel-group trial. Methods. Healthy non-selected participants were randomized to achieve cold-exposure 1 hour/day, or to avoid any sense of feeling cold, for 6 weeks. Metabolic rate (MR) was measured by indirect calorimetry before and after acute cold-exposure with cold vests and ingestion of cold water. The BAT volumes in the supraclavicular region were measured with magnetic resonance imaging (MRI). Results. Twenty-eight participants were recruited, 12 were allocated to controls and 16 to cold-exposure. Two participants in the cold group dropped out and one was excluded. Both the non-stimulated and the cold-stimulated MR were lowered within the group randomized to avoid cold (MR at room temperature from 1841 +/- 199 kCal/24 h to 1795 +/- 213 kCal/24 h, p = 0.047 cold-activated MR from 1900 +/- 150 kCal/24 h to 1793 +/- 215 kCal/24 h, p = 0.028). There was a trend towards increased MR at room temperature following the intervention in the cold-group (p = 0.052). The difference between MR changes by the interventions between groups was statistically significant (p = 0.008 at room temperature, p = 0.032 after cold-activation). In an on-treatment analysis after exclusion of two participants that reported >= 8 days without cold-exposure, supraclavicular BAT volume had increased in the cold-exposure group (from 0.0175 +/- 0.015 1 to 0.0216 +/- 0.014 1, p = 0.049). Conclusions. We found evidence for plasticity in metabolic rate by avoiding to freeze compared with cold-exposure in a randomized setting in non-selected humans.
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| 138. |
- Romu, Thobias, et al.
(författare)
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Characterization of Brown Adipose Tissue by Water-Fat Separated Magnetic Resonance Imaging
- 2015
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Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley. - 1053-1807 .- 1522-2586. ; 42:6, s. 1639-1645
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Tidskriftsartikel (refereegranskat)abstract
- Background: To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long echo time, dual-echo Dixon imaging protocol. Methods: A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by using the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 48 or 22 degrees C for 5 days. The rats were then scanned in a 70 cm bore 3.0 Tesla MRI scanner and a human dual energy CT. Interscapular, paraaortal, and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots. Results: The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (P< 0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (P=0.0064) and significantly larger iBAT and prBAT volumes (P=0.0017) were observed in the cold stimulated rats. Conclusion: The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism.
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| 139. |
- Romu, Thobias, 1984-
(författare)
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Fat-Referenced MRI : Quantitative MRI for Tissue Characterization and Volume Measurement
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The amount and distribution of adipose and lean tissues has been shown to be predictive of mortality and morbidity in metabolic disease. Traditionally these risks are assessed by anthropometric measurements based on weight, length, girths or the body mass index (BMI). These measurements are predictive of risks on a population level, where a too low or a too high BMI indicates an increased risk of both mortality and morbidity. However, today a large part of the world’s population belongs to a group with an elevated risk according to BMI, many of which will live long and healthy lives. Thus, better instruments are needed to properly direct health-care resources to those who need it the most.Medical imaging method can go beyond anthropometrics. Tomographic modalities, such as magnetic resonance imaging (MRI), can measure how we have stored fat in and around organs. These measurements can eventually lead to better individual risk predictions. For instance, a tendency to store fat as visceral adipose tissue (VAT) is associated with an increased risk of diabetes type 2, cardio-vascular disease, liver disease and certain types of cancer. Furthermore, liver fat is associated with liver disease, diabetes type 2. Brown adipose tissue (BAT), is another emerging component of body-composition analysis. While the normal white adipose tissue stores fat, BAT burns energy to produce heat. This unique property makes BAT highly interesting, from a metabolic point of view.Magnetic resonance imaging can both accurately and safely measure internal adipose tissue compartments, and the fat infiltration of organs. Which is why MRI is often considered the reference method for non-invasive body-composition analysis. The two major challenges of MRI based body-composition analysis are, the between-scanner reproducibility and a cost-effective analysis of the images. This thesis presents a complete implementation of fat-referenced MRI, a technique that produces quantitative images that can increase both inter-scanner and automation of the image analysis.With MRI, it is possible to construct images where water and fat are separated into paired images. In these images, it easy to depict adipose tissue and lean tissue structures. This thesis takes water-fat MRI one step further, by introducing a quantitative framework called fat-referenced MRI. By calibrating the image using the subjects' own adipose tissue (paper II), the otherwise non-quantitative fat images are made quantitative. In these fat-referenced images it is possible to directly measure the amount of adipose tissue in different compartments. This quantitative property makes image analysis easy and accurate, as lean and adipose tissues can be separated on a sub-voxel level. Fat-referenced MRI further allows the quantification and characterization of BAT.This thesis work starts by formulating a method to produce water-fat images (paper I) based on two gradient recall images, i.e.\ 2-point Dixon images (2PD). It furthers shows that fat-referenced 2PD images can be corrected for T2*, making the 2PD body-composition measurements comparable with confounder-corrected Dixon measurements (paper III}).Both the water-fat separation method and fat image calibration are applied to BAT imaging. The methodology is first evaluated in an animal model, where it is shown that it can detect both BAT browning and volume increase following cold acclimatization (paper IV). It is then applied to postmortem imaging, were it is used to locate interscapular BAT in human infants (paper V). Subsequent analysis of biopsies, taken based on the MRI images, showed that the interscapular BAT was of a type not previously believed to exist in humans. In the last study, fat-referenced MRI is applied to BAT imaging of adults. As BAT structures are difficult to locate in many adults, the methodology was also extended with a multi-atlas segmentation methods (paper VI).In summary, this thesis shows that fat-referenced MRI is a quantitative method that can be used for body-composition analysis. It also shows that fat-referenced MRI can produce quantitative high-resolution images, a necessity for many BAT applications.
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