Now showing items 21-30 of 30

    • Real-Time Chest Compression Quality Measurements by Smartphone Camera 

      Meinich-Bache, Øyvind; Engan, Kjersti; Birkenes, Tonje Søraas; Myklebust, Helge (Journal article; Peer reviewed, 2018-10)
      Out-of-hospital cardiac arrest (OHCA) is recognized as a global mortality challenge, and digital strategies could contribute to increase the chance of survival. In this paper, we investigate if cardiopulmonary resuscitation ...
    • Safer Births - Using Deep Neural Networks on Fetal Heart Rate Signals 

      Berntsen, Stian (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      Infant death is a big issue, especially in Africa and parts of Asia where between 24 and 30 [21] in every thousand do not survive the first month. In Europe this number is only 5.9 in every thousand. Reading fetal heart ...
    • Segmentation of infarcted regions in Perfusion CT images by 3D deep learning 

      Tomasetti, Luca (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06)
      This thesis explores different Convolutional Neural Network (CNN) approaches to classify and segment infarcted regions from images taken through a Computed Tomography Perfusion (CTP) from patients of the Stavanger’s hospital ...
    • Semi-Supervised Image Segmentation of Medical Data 

      Dalheim, Ove Nicolai (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 

      Wetteland, Rune; Dalheim, Ove Nicolai; Kvikstad, Vebjørn; Janssen, Emiel; Engan, Kjersti (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 ...
    • Signal Processing for Newborn Survival : from labour to resuscitation 

      Urdal, Jarle (PhD thesis UiS;, Doctoral thesis, 2020-08)
      Stillbirths are a worldwide challenge, with an estimated 2.6 million stillbirths in 2015, of these 1.3 million are estimated to have died during labour and birth, i.e. fresh stillbirth. In addition to the 2.6 million, one ...
    • Synaptic Vesicle Detection in Microscopy Images using Convolutional Neural Network and Compressed Sensing 

      Tofteberg, Simen Walmestad (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)
      In response to stressful situations, the body activates its sympathetic nervous system with the sudden release of hormones. This increases the presence of adrenaline and noradrenaline which improves muscle strength and ...
    • Telephone CPR Instructions in Cardiac Arrest 

      Hognestad, Ruth (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)
      This thesis focus on developing a dataset of recordings between a caller and a dispatcher from Emergency Communication Centre during situations involving cardiac arrest. It also focused on developing and implementing a ...
    • The localization and characterization of ischemic scars in relation to the infarct related coronary artery assessed by cardiac magnetic resonance and a novel automatic postprocessing method 

      Woie, Leik; Engan, Kjersti; Eftestøl, Trygve; Larsen, Alf Inge; Ørn, Stein (Journal article; Peer reviewed, 2015-09)
      Aims . The correspondence between the localization and morphology of ischemic scars and the infarct related artery (IRA) by use of cardiac magnetic resonance imaging and a novel automatic postprocessing method. Methods ...
    • Videodeteksjon av hjerte- og respirasjonsrate 

      Meinich-Bache, Øyvind (Masteroppgave/UIS-TN-IDE/2016;, Master thesis, 2016-06-15)
      I rapporten er mulighetene en har ved å benytte video til deteksjon av hjerte- og respirasjonsrate på nyfødte babyer utforsket. Datamaterialet som inngår i forsøkene og utviklingen av algoritmene er hentet inn ved Universitet ...