| 1. |
- Candefjord, Stefan, 1981, et al.
(author)
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Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations
- 2017
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In: Medical and Biological Engineering and Computing. - : Springer Science and Business Media LLC. - 1741-0444 .- 0140-0118. ; 55:8, s. 1177-1188
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Journal article (peer-reviewed)abstract
- Traumatic brain injury is the leading cause of death and severe disability for young people and a major public health problem for elderly. Many patients with intracranial bleeding are treated too late, because they initially show no symptoms of severe injury and are not transported to a trauma center. There is a need for a method to detect intracranial bleedings in the prehospital setting. In this study, we investigate whether broadband microwave technology (MWT) in conjunction with a diagnostic algorithm can detect subdural hematoma (SDH). A human cranium phantom and numerical simulations of SDH are used. Four phantoms with SDH 0, 40, 70 and 110 mL are measured with a MWT instrument. The simulated dataset consists of 1500 observations. Classification accuracy is assessed using fivefold cross-validation, and a validation dataset never used for training. The total accuracy is 100 and 82–96 % for phantom measurements and simulated data, respectively. Sensitivity and specificity for bleeding detection were 100 and 96 %, respectively, for the simulated data. SDH of different sizes is differentiated. The classifier requires training dataset size in order of 150 observations per class to achieve high accuracy. We conclude that the results indicate that MWT can detect and estimate the size of SDH. This is promising for developing MWT to be used for prehospital diagnosis of intracranial bleedings.
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| 2. |
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| 3. |
- Fhager, Andreas, 1976, et al.
(author)
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3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology
- 2019
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In: Sensors. - : MDPI AG. - 1424-8220. ; 19:16
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Journal article (peer-reviewed)abstract
- Early, preferably prehospital, detection of intracranial bleeding after trauma or stroke would dramatically improve the acute care of these large patient groups. In this paper, we use simulated microwave transmission data to investigate the performance of a machine learning classification algorithm based on subspace distances for the detection of intracranial bleeding. A computational model, consisting of realistic human head models of patients with bleeding, as well as healthy subjects, was inserted in an antenna array model. The Finite-Difference Time-Domain (FDTD) method was then used to generate simulated transmission coefficients between all possible combinations of antenna pairs. These transmission data were used both to train and evaluate the performance of the classification algorithm and to investigate its ability to distinguish patients with versus without intracranial bleeding. We studied how classification results were affected by the number of healthy subjects and patients used to train the algorithm, and in particular, we were interested in investigating how many samples were needed in the training dataset to obtain classification results better than chance. Our results indicated that at least 200 subjects, i.e., 100 each of the healthy subjects and bleeding patients, were needed to obtain classification results consistently better than chance (p < 0.05 using Student's t-test). The results also showed that classification results improved with the number of subjects in the training data. With a sample size that approached 1000 subjects, classifications results characterized as area under the receiver operating curve (AUC) approached 1.0, indicating very high sensitivity and specificity.
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| 4. |
- Fhager, Andreas, 1976, et al.
(author)
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FDTD based simulation study of a classification based hemorrhagic stroke detector
- 2018
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In: IET Conference Publications. - : Institution of Engineering and Technology. ; 2018:CP741
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Conference paper (peer-reviewed)abstract
- The possibility to detect intracranial bleedings caused by stroke or head trauma in a prehospital setting would be a major breakthrough in the strive to deliver the best possible care for these patients. Our research is focused on developing a microwave based diagnostic system for prehospital use, which is capable of detecting intracranial bleedings. This paper contains a numerical simulation study to investigate the detection capability of a machine learning algorithm and its performance for differentiating hemorrhagic stroke from patients with no bleeding. The goal is to assess the performance of the detection algorithm as a function of the number of patients included in the training phase. The results show that this approach is feasible, but that it requires one thousand patients for training the algorithm, in order to reach a detection rate with AUC values approaching 0.9.
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| 5. |
- Fhager, Andreas, 1976, et al.
(author)
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Microwave Diagnostics Ahead: Saving Time and the Lives of Trauma and Stroke Patients
- 2018
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In: IEEE Microwave Magazine. - 1527-3342 .- 1557-9581. ; 19:3, s. 78-90
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Journal article (peer-reviewed)abstract
- Microwave technology has the potential to revolutionize how, when, and what care can be delivered to patients with acute, life-threatening medical conditions. The prospects are that microwave systems can both improve diagnostic ability and accuracy and enable earlier diagnosis. Early diagnosis is a key factor in acute situations, especially when breathing and circulation are affected. Conventional imaging modalities used for diagnostics, such as magnetic resonance imaging (MRI) and X-ray computed tomography (CT), are powerful but normally available only at hospitals.
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| 6. |
- Fhager, Andreas, 1976, et al.
(author)
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Microwave Technology in Medical Diagnostics and Treatment
- 2015
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In: 2015 Ieee Mtt-S International Microwave Workshop Series on Rf and Wireless Technologies for Biomedical and Healthcare Applications. - New York : Ieee. - 9781479985432 ; , s. 133-134
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Book chapter (other academic/artistic)abstract
- There is a great need for novel diagnostics and treatment tools in today's healthcare. In this paper we describe our development and progress in novel microwave based diagnostics and treatment applications. The target applications are stroke diagnostics, breast cancer detection and microwave hyperthermia.
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| 7. |
- Fhager, Andreas, 1976, et al.
(author)
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Numerical study on image reconstructions of breast models in different matching liquids
- 2017
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In: 2016 IEEE Conference on Antenna Measurements and Applications, CAMA 2016, Syracuse, United States, 23-27 October 2016.
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Conference paper (peer-reviewed)abstract
- In this paper a numerical study of the reconstruction of breast models in different matching media is made. The purpose is to determine a reconstruction scheme and investigate how the reconstruction result is affected by different choice of matching medium. The present study is based on data generated on generic breast phantoms as well as realistic phantoms. A time domain FDTD based reconstruction method was used. We conclude that the choice of matching liquid in imaging systems is important and largely affects the image quality, and that adaptations in the imaging algorithm itself can make the imaging result more robust and allow for a wider range of potential imaging scenarios.
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| 8. |
- Fhager, Andreas, 1976, et al.
(author)
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On the use of microwave based thermal monitoring in hyperthermia
- 2015
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In: 9th European Conference on Antennas and Propagation, EuCAP 2015, Lisbon, Portugal, 13-17 May 2015. - 9788890701856
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Conference paper (peer-reviewed)abstract
- Clinical results show that microwave based hyperthermia can dramatically improve the treatment outcome if combined with radiation and chemo therapy. During hyperthermia treatment it is necessary to monitor the heating in order to ensure that therapeutic temperatures are reached in the tumour, as well as to monitor hot-spots in non-tumour areas. Microwave imaging technology has the potential to be sensitive to changes in the dielectric tissue parameters caused by the hyperthermia heating. In this paper we discuss the feasibility for a combined heating / temperature monitoring system based entirely on microwave technology.
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| 9. |
- Fhager, Andreas, 1976, et al.
(author)
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Reconstrunction strategies for microwave imaging of breast; Reconstructions constrained to the breast domain
- 2017
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In: 2017 1st IEEE MTT-S International Microwave Bio Conference, IMBioC 2017. - 9781538617137
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Conference paper (peer-reviewed)abstract
- In this paper an image reconstruction system and an algorithm for image reconstruction is developed and studied. The purpose is to determine and optimize a reconstruction scheme that is suitable for microwave imaging of breasts, with the purpose to diagnose breast cancer tumors. The present study is based on data generated from realistic breast models and in particular the use of different matching medium and constraining the reconstruction to within the breast region is studied. A time domain FDTD based reconstruction method is used. We conclude that the choice of matching liquid in imaging systems is important and largely affects the image quality, there is also a clear advantage of using a constrained reconstruction domain. A general conclusion is that particular adaptations in the imaging scheme can make the imaging result more robust and allow for a wider range of potential imaging scenarios.
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| 10. |
- Fhager, Andreas, 1976, et al.
(author)
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Reducing computational burden in the gradient calculation of a time-domain microwave image reconstruction algorithm
- 2018
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In: 2018 IEEE Conference on Antenna Measurements and Applications, CAMA 2018. - 9781538657959
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Conference paper (peer-reviewed)abstract
- Microwave image reconstruction is usually made with very computationally demanding algorithms. In this work a time domain image reconstruction algorithm is investigated. With this algorithm the memory requirement for the gradient calculation easily can expand beyond what can be fitted into the RAM memory of a computer. As a consequence, the hard drive has to be used for intermediate storage of computation data. This has serious implications on the execution time of the reconstruction algorithm. In this work we investigate what effect a reduction of the number of data points in the gradient calculation has on the reconstruction accuracy. The results show that significant reduction is possible without apparent effect on the reconstructed image.
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