WorldCat Identities

Linköpings universitet Institutionen för medicinsk teknik

Overview
Works: 260 works in 278 publications in 2 languages and 272 library holdings
Roles: Publisher, pub, Editor, Other
Publication Timeline
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Most widely held works by Linköpings universitet
Elektromagnetiska fält i svensk svets- och stålindustri - 1 : En översikt - ASF 131 by P Lövsund( Book )

2 editions published in 1975 in Swedish and held by 2 WorldCat member libraries worldwide

Elektromagnetiska fält i svensk svets- och stålindustri - 2 : Punktsvetsning och ventrikulära extraslag : en undersökning vid LME, Karlskrona - ASF 131 by P Lövsund( Book )

2 editions published in 1975 in Swedish and held by 2 WorldCat member libraries worldwide

Elektromagnetiska fält i svensk svets- och stålindustri by P Lövsund( Book )

2 editions published in 1976 in Swedish and held by 2 WorldCat member libraries worldwide

MRI based radiotherapy planning and pulse sequence optimization by Jens Sjölund( Book )

2 editions published in 2015 in English and held by 2 WorldCat member libraries worldwide

Scalability and semantic sustainability in electronic health record systems by Erik Sundvall( Book )

2 editions published in 2013 in English and held by 2 WorldCat member libraries worldwide

Robust Image Registration for Improved Clinical Efficiency Using Local Structure Analysis and Model-Based Processing by Daniel Forsberg( Book )

2 editions published in 2013 in English and held by 2 WorldCat member libraries worldwide

Elektromagnetiska fält i svensk svets- och stålindustri by P Lövsund( Book )

2 editions published in 1976 in Swedish and held by 2 WorldCat member libraries worldwide

Fluorescence spectroscopy for quantitative demarcation of glioblastoma using 5-aminolevulinic acid by Neda Haj-Hosseini( )

2 editions published in 2012 in English and held by 2 WorldCat member libraries worldwide

Total resection of glioblastoma, the highly malignant brain tumor, is difficult to accomplish due to its diffuse growth and similarity to the surrounding brain tissue. A total resection is proven to increase patient survival. The aim of this thesis was to evaluate fiber-optical based fluorescence spectroscopy for quantitative demarcation of malignant brain tumors during the surgery. Five-aminolevulinic acid (5-ALA) was used as a fluorescence contrast agent that accumulated as protoporphyrin IX (PpIX) in the tumor. The method was evaluated at the Department of Neurosurgery, Linköping University Hospital. The patients (n = 22) received an oral dose of 5 mg/kg body weight 5-ALA two hours prior to craniotomy. Measurements with a developed fluorescence spectroscopy system were performed under the general procedure of surgery. The collected fluorescence spectra were quantified by defining a fluorescence ratio and the main challenges of measuring and quantifying spectra were investigated. The fluorescence ratio was compared to visual diagnosis of the surgeon, histopathological examination and ultrasound-based neuronavigation. The main challenges of using a fluorescence spectroscopy system in the operating room were the disturbing ambient light, photobleaching and blood interference which affect the signal quantification. The superimposition of ambient light was removed by modulating the system. Using principal component analysis (PCA) the photobleaching sequences could be described by three spectral components of autofluorescence, PpIX fluorescence and blue-shift. To investigate the photobleaching induced prior to the measurements, a dynamic model was developed based on the PCA derived spectral components. Modulation and increased power of the excitation light resulted in a faster photobleaching; however, photobleaching was saturated at higher excitation powers. The system was adjusted to induce minimal photobleaching. In addition, effect of blood absorption on the fluorescence spectrum was investigated experimentally by placing blood drops on skin and theoretically by using Beer-Lambert law. The theoretical model was used to compensate for the distorted fluorescence ratio. According to the theoretical model of blood interference, a total 300 µm blood layer blocked the brain fluorescence signal totally and when the fluorescence signal was partially blocked, the fluorescence ratio was overestimated. The fluorescence ratio was corrected for blood layers thinner than 50 µm. The tissue in and around the tumor was categorized into necrosis, low and high grade tumor and gliosis. The median fluorescence ratio confirmed with histopathological examination (n = 45) had a lower fluorescence ratio for low grade malignancies (0.3) than high grade malignancies (2.4) (p < 0.05). Gliosis (1.6) and necrosis (1.0) showed a moderate fluorescence ratio. Ultrasound-based navigation in combination with fluorescence spectroscopy showed improvement in the results; however, a more extensive study is needed to confirm benefits of the method combination. In conclusion, fluorescence spectroscopy of 5-ALA induced PpIX provided an objective method for differentiating tumor from the healthy tissue intra-operatively. Fluorescence ratios were indicative of tissue type and tumor malignancy degree
Image analysis and visualization of the human mastoid air cell system by Olivier Cros( Book )

2 editions published in 2015 in English and held by 2 WorldCat member libraries worldwide

A Global Linear Optimization Framework for Adaptive Filtering and Image Registration by Johansson Gustaf( Book )

2 editions published in 2015 in English and held by 2 WorldCat member libraries worldwide

Integrating Socially Assistive Robots into Japanese Nursing Care by MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 2020 30th Medical Informatics Europe Conference( )

2 editions published in 2020 in English and held by 2 WorldCat member libraries worldwide

This paper presents experiences of integrating assistive robots in Japanese nursing care through semi-structured interviews and site observations at three nursing homes in Japan during the spring of 2019. The study looked at experiences with the robots Paro, Pepper, and Qoobo. The goal was to investigate and evaluate the current state of using robots in the nursing care context, firsthand experiences with intended and real use, as well as response from the elderly and nursing staff. The qualitative analysis results pointed out user satisfaction, adjusted purpose, therapeutic and entertaining effects. Potentials of robots to assist in elderly care is advantageous. Limitations currently relate to the lack of ways to fully utilized and integrate robots
Algorithms for magnetic resonance imaging in radiotherapy by Jens Sjölund( )

2 editions published in 2018 in English and held by 2 WorldCat member libraries worldwide

Radiotherapy plays an increasingly important role in cancer treatment, and medical imaging plays an increasingly important role in radiotherapy. Magnetic resonance imaging (MRI) is poised to be a major component in the development towards more effective radiotherapy treatments with fewer side effects. This thesis attempts to contribute in realizing this potential. Radiotherapy planning requires simulation of radiation transport. The necessary physical properties are typically derived from CT images, but in some cases only MR images are available. In such a case, a crude but common approach is to approximate all tissue properties as equivalent to those of water. In this thesis we propose two methods to improve upon this approximation. The first uses a machine learning approach to automatically identify bone tissue in MR. The second, which we refer to as atlas-based regression, can be used to generate a realistic, patient-specific, pseudo-CT directly from anatomical MR images. Atlas-based regression uses deformable registration to estimate a pseudo-CT of a new patient based on a database of aligned MR and CT pairs. Cancerous tissue has a different structure from normal tissue. This affects molecular diffusion, which can be measured using MRI. The prototypical diffusion encoding sequence has recently been challenged with the introduction of more general gradient waveforms. One such example is diffusional variance decomposition (DIVIDE), which allows non-invasive mapping of parameters that reflect variable cell eccentricity and density in brain tumors. To take full advantage of such more general gradient waveforms it is, however, imperative to respect the constraints imposed by the hardware while at the same time maximizing the diffusion encoding strength. In this thesis we formulate this as a constrained optimization problem that is easily adaptable to various hardware constraints. We demonstrate that, by using the optimized gradient waveforms, it is technically feasible to perform whole-brain diffusional variance decomposition at clinical MRI systems with varying performance. The last part of the thesis is devoted to estimation of diffusion MRI models from measurements. We show that, by using a machine learning framework called Gaussian processes, it is possible to perform diffusion spectrum imaging using far fewer measurements than ordinarily required. This has the potential of making diffusion spectrum imaging feasible even though the acquisition time is limited. A key property of Gaussian processes, which is a probabilistic model, is that it comes with a rigorous way of reasoning about uncertainty. This is pursued further in the last paper, in which we propose a Bayesian reinterpretation of several of the most popular models for diffusion MRI. Thanks to the Bayesian interpretation it possible to quantify the uncertainty in any property derived from these models. We expect this will be broadly useful, in particular in group analyses and in cases when the uncertainty is large
Fat-Referenced MRI : Quanitaive MRI for Tissue Characterizaion and Volume Measurement by Thobias Romu( )

2 editions published in 2018 in English and held by 2 WorldCat member libraries worldwide

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 T 2 *, 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
Smartware electrodes for ECG measurements Design, evaluation and signal processing by Linda Rattfält( Book )

2 editions published in 2013 in English and held by 2 WorldCat member libraries worldwide

Testing of Doppler ultrasound systems by Andrew Walker( )

2 editions published in 2009 in English and held by 2 WorldCat member libraries worldwide

Blood and tissue velocities are measured and analyzed in cardiac, vascular, and other applications of diagnostic ultrasound. Errors in system performance might give invalid measurements. We developed two moving string test targets and a rotating cylinder phantom (Doppler phantoms) to characterize Doppler ultrasound systems. These phantoms were initially used to measure such variables as sample volume dimensions, location of the sample volume, and the performance of the spectral analysis. Later, specific tests were designed and performed to detect errors in signal processing, causing time delays and inaccurate velocity estimation in all Doppler modes. In cardiac motion pattern even time delays as short as 30 ms may have clinical relevance. These delays can be obtained with echocardiography by using flow and tissue Doppler and M-mode techniques together with external signals (e.g., electrocardiography (ECG) and phonocardiography). If one or more of these signals are asynchronous in relation to the other signals, an incorrect definition of cardiac time intervals may occur. To determine if such time delays in signal processing are a serious problem, we tested four commercial ultrasound systems. We used the Doppler string phantom and the rotating cylinder phantom to obtain test signals. We found time delays of up to 90 ms in one system, whereas delays were mostly short in the other systems. Further, the time delays varied relative to system settings. In two-dimensional (2D) Doppler the delays were closely related to frame rate. To determine the accuracy in velocity calibration, we tested the same four ultrasound systems using the Doppler phantoms to obtain test signals for flow (PW) and tissue (T-PW) pulse Doppler and for continuous wave (CW) Doppler. The ultrasound systems were tested with settings and transducers commonly used in cardiac applications. In two systems, the observed errors were mostly close to zero, whereas one system systematically overestimated velocity by an average of 4.6%. The detected errors are mostly negliable in clinical practice but might be significant in certain cases and research applications
Evaluation of Six Phase Encoding Based Susceptibility Distortion Correction Methods for Diffusion MRI by Xuan Gu( )

2 editions published in 2019 in English and held by 2 WorldCat member libraries worldwide

Purpose: Susceptibility distortions impact diffusion MRI data analysis and is typically corrected during preprocessing. Correction strategies involve three classes of methods: registration to a structural image, the use of a fieldmap, or the use of images acquired with opposing phase encoding directions. It has been demonstrated that phase encoding based methods outperform the other two classes, but unfortunately, the choice of which phase encoding based method to use is still an open question due to the absence of any systematic comparisons. Methods: In this paper we quantitatively evaluated six popular phase encoding based methods for correcting susceptibility distortions in diffusion MRI data. We employed a framework that allows for the simulation of realistic diffusion MRI data with susceptibility distortions. We evaluated the ability for methods to correct distortions by comparing the corrected data with the ground truth. Four diffusion tensor metrics (FA, MD, eigenvalues and eigenvectors) were calculated from the corrected data and compared with the ground truth. We also validated two popular indirect metrics using both simulated data and real data. The two indirect metrics are the difference between the corrected LR and AP data, and the FA standard deviation over the corrected LR, RL, AP, and PA data. Results: We found that DR-BUDDI and TOPUP offered the most accurate and robust correction compared to the other four methods using both direct and indirect evaluation metrics. EPIC and HySCO performed well in correcting b 0 images but produced poor corrections for diffusion weighted volumes, and also they produced large errors for the four diffusion tensor metrics. We also demonstrate that the indirect metric (the difference between corrected LR and AP data) gives a different ordering of correction quality than the direct metric. Conclusion: We suggest researchers to use DR-BUDDI or TOPUP for susceptibility distortion correction. The two indirect metrics (the difference between corrected LR and AP data, and the FA standard deviation) should be interpreted together as a measure of distortion correction quality. The performance ranking of the various tools inferred from direct and indirect metrics differs slightly. However, across all tools, the results of direct and indirect metrics are highly correlated indicating that the analysis of indirect metrics may provide a good proxy of the performance of a correction tool if assessment using direct metrics is not feasible
Elektromagnetiska fält i svensk svets- och stålindustri by P Lövsund( Book )

2 editions published in 1976 in Swedish and held by 2 WorldCat member libraries worldwide

Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images by Marco Domenico Cirillo( )

1 edition published in 2021 in English and held by 1 WorldCat member library worldwide

This paper illustrates the efficacy of an artificial intelligence (AI) (a convolutional neural network, based on the U-Net), for the burn-depth assessment using semantic segmentation of polarized high-performance light camera images of burn wounds. The proposed method is evaluated for paediatric scald injuries to differentiate four burn wound depths: superficial partial-thickness (healing in 0-7 days), superficial to intermediate partial-thickness (healing in 8-13 days), intermediate to deep partial-thickness (healing in 14-20 days), deep partial-thickness (healing after 21 days) and full-thickness burns, based on observed healing time. In total 100 burn images were acquired. Seventeen images contained all 4 burn depths and were used to train the network. Leave-one-out cross-validation reports were generated and an accuracy and dice coefficient average of almost 97% was then obtained. After that, the remaining 83 burn-wound images were evaluated using the different network during the cross-validation, achieving an accuracy and dice coefficient, both on average 92%. This technique offers an interesting new automated alternative for clinical decision support to assess and localize burn-depths in 2D digital images. Further training and improvement of the underlying algorithm by e.g., more images, seems feasible and thus promising for the future
Elderly patients with COPD require more health care than elderly heart failure patients do in a hospital-based home care setting by Lennart Persson( )

1 edition published in 2019 in English and held by 1 WorldCat member library worldwide

Background: Elderly patients with advanced stages of COPD or chronic heart failure (CHF) often require hospitalization due to exacerbations. We hypothesized that telemonitoring supported by hospital-based home care (HBHC) would detect exacerbations early, thus, reducing the number of hospitalization. We also speculated that patients with advanced COPD or CHF would present differences regarding exacerbation frequency and the need of HBHC. Methods: The Health Diary system, based on digital pen technology, was employed. Patients aged amp;gt;= 65 years with amp;gt;= 2 hospitalizations the previous year were included. Exacerbations were categorized and treated as either COPD or CHF exacerbation by an experienced physician. All HBHC contacts (home visits or telephone consultations) were registered. Results: Ninety-four patients with advanced diseases were enrolled (36 COPD and 58 CHF subjects) of which 53 subjects (19 COPD and 34 CHF subjects) completed the 1-year study period. Death was the major reason for not finalizing the study. Compared to the 1-year prior inclusion, the intervention significantly reduced hospitalization. Although COPD subjects were younger with less comorbidity, exacerbations and HBHC contacts were significantly greater in this group. Conclusions: COPD subjects exhibit exacerbations more frequently, mainly due to disease characteristics, thus, demanding much more HBHC
Effects of training on truck drivers interaction with cyclists in a right turn by Katja Kircher( )

1 edition published in 2020 in English and held by 1 WorldCat member library worldwide

With encounters between trucks and cyclists still being a major safety issue and physical as well as technological improvements far from ubiquitous implementation, training truck drivers in anticipatory driving to improve their interaction with cyclists may be a way forward. After a baseline drive in an urban environment, truck drivers inexperienced with urban driving received a dedicated training on anticipatory driving, followed by another drive along the same route several weeks later. The drivers were also interviewed about their opinion about the training. The drivers behaviour changed from before to after training, resulting in a better speed management in general, and a more intensive monitoring of the cyclists. There were also some improvements with respect to the placement in relation to the cyclist, but this effect was limited mainly because truck drivers performed well already before the training. The observed results correspond well to the opinions and feelings about the training that were reported by the drivers in the interview. Thus, driver training can possibly be one contributor to an increase in safety in urban areas
 
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Alternative Names
Department of Biomedical Engineering

IMT

Institutionen för medicinsk teknik, Linköpings universitet

Linköping University. Department of Biomedical Engineering

Linköpings universitet Institutionen för medicinsk teknik

Linköpings universitet. Tekniska högskolan. Institutionen för medicinsk teknik

Northwestern University Department of Biomedical Engineering academic department

Universitetet i Linköping Institutionen för medicinsk teknik

Languages
English (27)

Swedish (10)