Blar i Department of Electrical and Computer Engineering (TN-IDE) på emneord "VDP::Teknologi: 500::Medisinsk teknologi: 620"
Viser treff 1-20 av 23
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Adapt and Generalize Deep Learning Methods for Activity Recognition on Newborn Resuscitation Videos
(Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)Low- and middle-income countries have nearly 99 % of deaths of children under 28 days. Complications during childbirths, such as birth asphyxia, account for most of these deaths. To prevent this, strengthening the quality ... -
Artifact Correction in Short-Term HRV during Strenuous Physical Exercise
(Peer reviewed; Journal article, 2020-11)Heart rate variability (HRV) analysis can be a useful tool to detect underlying heart or even general health problems. Currently, such analysis is usually performed in controlled or semi-controlled conditions. Since many ... -
Automated Grading of Bladder Cancer using Deep Learning
(PhD thesis UiS;, Doctoral thesis, 2022-02)Urothelial carcinoma is the most common type of bladder cancer and is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, ... -
Automatic AI-Driven segmentation of Acute Ischemic Stroke Regions with CT Perfusion Images
(PhD thesis UiS;, Doctoral thesis, 2023)This thesis investigates artificial intelligence (AI) methodologies to automatically delineate ischemic areas of brain Computed Tomography Perfusion (CTP) scans acquired at hospital admission in patients suspected of acute ... -
Automatic diagnostic tool for predicting cancer grade in bladder cancer patients using deep learning
(Peer reviewed; Journal article, 2021-08)The most common type of bladder cancer is urothelial carcinoma, which is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, ... -
Automatic Video Analysis in Resuscitation
(PhD thesis UiS;, Doctoral thesis, 2020-01)This thesis investigates possibilities for applying automatic video analysis in the medical context of resuscitation of a patient. Two situations are investigated: 1) Out-of-hospital cardiac arrest (OHCA) where there is a ... -
CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke
(Peer reviewed; Journal article, 2023)Stroke is the second leading cause of death worldwide, and around 87 % of strokes are ischemic strokes. Accurate and rapid prediction techniques for identifying ischemic regions, including dead tissue (core) and potentially ... -
The devil is in the details: Whole Slide Image acquisition and processing for artifacts detection, color variation, and data augmentation: A review.
(Peer reviewed; Journal article, 2022)Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and ... -
Exploring Generative Adversarial Networks to Improve Prostate Segmentation on MRI
(Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-28)Prostate cancer is the second most occurring cancer and the sixth leading cause of cancer death among men worldwide. The number of cases is expected to increase dramatically due to population growth and increased expected ... -
Extended approach to sum of absolute differences method for improved identification of periods in biomedical time series
(Peer reviewed; Journal article, 2020-10)Time series are a common data type in biomedical applications. Examples include heart rate, power output, and ECG. One of the typical analysis methods is to determine longest period a subject spent over a given heart rate ... -
A Low-Cost Wireless Body Area Network for Human Activity Recognition in Healthy Life and Medical Applications
(Peer reviewed; Journal article, 2023)Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more ... -
Machine learning algorithms vs. thresholding to segment ischemic regions in patients with acute ischemic stroke
(Peer reviewed; Journal article, 2021-07)Objective: Computed tomography (CT) scan is a fast and widely used modality for early assessment in patients with symptoms of a cerebral ischemic stroke. CT perfusion (CTP) is often added to the protocol and is used by ... -
Multi-input segmentation of damaged brain in acute ischemic stroke patients using slow fusion with skip connection
(Peer reviewed; Journal article, 2022-03)Time is a fundamental factor during stroke treatments. A fast, automatic approach that segmentsthe ischemic regions helps treatment decisions. In clinical use today, a set of color-coded parametric maps generated from ... -
Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction
(Peer reviewed; Journal article, 2023-09)Heart rate variability (HRV) is the variation in time between successive heartbeats and can be used as an indirect measure of autonomic nervous system (ANS) activity. During physical exercise, movement of the measuring ... -
Prediction of Psychosis in Parkinson’s Patients using Machine Learning
(Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020)Parkinson’s disease is one of the most common neurological disorders with an estimated 6.3 million PD patients worldwide, which makes it a great threat to public health. Psychosis is a common symptom of Parkinson’s disease ... -
A probabilistic function to model the relationship between quality of chest compressions and the physiological response for patients in cardiac arrest
(Peer reviewed; Journal article, 2020) -
Regional Convolutional Neural Network for Cell Detection and Classification in Urinary Bladder Cancer
(Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)Bladder canceristhefourth most common type of cancer in men and the eighth in women. Patient treated for this cancer must be monitored for the rest of their live due to the recurrence of this disease.That need for monitoring ... -
Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks
(Peer reviewed; Journal article, 2020-05)Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The objective of this study was to design ... -
Semi-Supervised Image Segmentation of Medical Data
(Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020)Bladder cancer is the fourth most common cancer type in Norway, and tenth most common on a global scale. More and more tissue samples are sent to pathologists labs, increasing the workload and affecting the waiting time ... -
Semi-supervised tissue segmentation of histological images
(Peer reviewed; Journal article, 2020-09)Supervised learning of convolutional neural networks (CNN) used for image classification and segmentation has produced state-of-the art results, including in many medical image applications. In the medical field, making ...