Blar i UiS Brage på forfatter "Oppedal, Ketil"

Viser treff 1-20 av 24

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      Hult Karlson, Ådne; Berg, Stian Wiik (Master thesis, 2023)
      Staying in shape is important for physical and mental health. Adding squats to a regular workout routine is beneficial, but performing them correctly and determining the right number of repetitions can be challenging. A ...

    • 3D Masked Modelling Advances Lesion Classification in Axial T2w Prostate MRI 

      Fernandez Quilez, Alvaro; Andersen, Christoffer Gabrielsen; Eftestøl, Trygve Christian; Kjosavik, Svein Reidar; Oppedal, Ketil (Peer reviewed; Journal article, 2023)
      Masked Image Modelling (MIM) has been shown to be an efficient self-supervised learning (SSL) pre-training paradigm when paired with transformer architectures and in the presence of a large amount of unlabelled natural ...

    • A Multi-class Dementia Classification Assessment Utilizing GAN to Convert MRI Scans from the 1.5T Domain to the 3.0T Domain 

      Godal, Håvard (Master thesis, 2022)
      Dementia is the seventh leading cause of death among all diseases and increases rapidly. With 10 million new cases every year, research is crucial for finding a treatment to cure dementia in the future. Magnetic resonance ...

    • Association Between Amygdala Volume and Trajectories of Neuropsychiatric Symptoms in Alzheimer’s Disease and Dementia With Lewy Bodies 

      Jaramillo-Jiménez, Alberto; Melvær, Giil Lasse; Tovar-Rios, Diego Alejandro; Borda, Miguel Germán; Ferreira, Daniel; Brønnick, Kolbjørn Kallesten; Oppedal, Ketil; Aarsland, Dag (Peer reviewed; Journal article, 2021-07)
      Introduction: The amygdala is implicated in psychiatric illness. Even as the amygdala undergoes significant atrophy in mild dementia, amygdala volume is underexplored as a risk factor for neuropsychiatric symptoms ...

    • Classifying dementia using local binary patterns from different regions in magnetic resonance images 

      Oppedal, Ketil; Eftestøl, Trygve; Engan, Kjersti; Beyer, Mona K.; Aarsland, Dag (Journal article; Peer reviewed, 2015)
      Dementia is an evolving challenge in society, and no disease-modifying treatment exists. Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D ...

    • Clinical and neuroimaging prognostic markers in Alzheimer's Disease and Lewy Body Dementia: The role of muscle status and nutrition 

      Borda Borda, Miguel Germán (PhD thesis UiS;, Doctoral thesis, 2023)
      Alzheimer's Disease and Lewy body dementia are the two most common neurodegenerative dementias. They have a progressive course with devastating consequences for the people living with these diseases and their families, but ...

    • The combined effect of amyloid-β and tau biomarkers on brain atrophy in dementia with Lewy bodies 

      Abdelnour, Carla; Ferreira, Daniel; Oppedal, Ketil; Cavallin, Lena; Bousiges, Olivier; Wahlund, Lars Olof; Hort, Jakub; Nedelska, Zuzana; Padovani, Alessandro; Pilotto, Andrea; Bonanni, Laura; Kramberger, Milica Gregoric; Boada, Mercè; Westman, Eric; Pagonabarraga, Javier; Kulisevsky, Jaime; Blanc, Frédéric; Aarsland, Dag (Peer reviewed; Journal article, 2020-07)
      Background Alzheimer’s disease (AD)-related pathology is frequently found in patients with dementia with Lewy bodies (DLB). However, it is unknown how amyloid-β and tau-related pathologies influence neurodegeneration in ...

    • Conditional data generation for an improved diagnosis in prostate cancer 

      Parvez, Omer (Master thesis, 2021)
      Prostate Cancer is the second most common cancer in men worldwide, the fourth most commonly occurring cancer overall and the sixth leading cause of cancer death among men worldwide. Early detection of prostate cancer is ...

    • Data-assisted differential diagnosis of dementia by deep neural networks 

      Larsen, Simen Norrheim (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-29)
      There are currently 50 million people suffering from dementia worldwide. With an increasing life expectancy of the elderly, this number is expected to increase drastically over the next decade. With today's diagnosis of ...

    • Dementia classification using deep learning and texture analysis methods on magnetic resonance images 

      Risanger, Rune (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)
      Dementia is becoming an increasingly severe economical and socio-economical disease, as treatment is problematic, with different disease variants difficult to prevent and delay. With a rise in life expectancy, further ...

    • Early Detection of Alzheimer’s Disease using 3D Texture Features and 3D Convolutional Neural Networks from structural MRI 

      Moen, Ulrik (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06)
      In 2016 there was estimated that around 47 million people in the world were living with dementia, and this number were projected to increase to 131 million by 2050. Alzheimer’s disease is the most common type of dementia ...

    • Effects of purified anthocyanins in people at risk for dementia: Study protocol for a phase II randomized controlled trial 

      Khalifa, Khadija; Bergland, Anne Katrine; Sønnesyn, Hogne; Oppedal, Ketil; Oesterhus, Ragnhild; Dalen, Ingvild; Larsen, Alf Inge; Fladby, Tormod; Brooker, Helen; Wesnes, Keith A.; Ballard, Clive; Aarsland, Dag (Peer reviewed; Journal article, 2020)
      Background: The number of people with dementia is increasing, with huge challenges for society and health-care systems. There are no disease-modifying therapies available. There is, therefore, an urgent need to identify ...

    • Exploring Generative Adversarial Networks to Improve Prostate Segmentation on MRI 

      Larsen, Steinar Valle (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 ...

    • Federated Learning for Dementia Classification in a European Multicentre Dementia Study 

      Hesseberg, Ruben; Minne, Petter (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-07-15)
      Every year around 10 million people are diagnosed with dementia worldwide. Higher life expectancy and population growth could inflate this number even further in the near future. Currently the diagnostic process of dementia ...

    • MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies 

      Inguanzo, Anna; Poulakis, Konstantinos; Mohanty, Rosaleena; Schwarz, Christopher G.; Przybelski, Scott A.; Diaz-Galvan, Patricia; Lowe, Val J.; Boeve, Bradley F.; Lemstra, Afina W.; van de Beek, Marleen; van der Flier, Wiesje; Barkhof, Frederik; Blanc, Frederic; Loureiro de Sousa, Paulo; Philippi, Nathalie; Cretin, Benjamin; Demuynck, Catherine; Nedelska, Zuzana; Hort, Jakub; Segura, Barbara; Junque, Carme; Oppedal, Ketil; Aarsland, Dag; Westman, Eric; Kantarci, Kejal; Ferreira, Daniel (Peer reviewed; Journal article, 2023)
      Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) ...

    • Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data 

      Abdelnour, Carla; Ferreira, Daniel; van de Beek, Marleen; Cedres, Nira; Oppedal, Ketil; Cavallin, Lena; Blanc, Frédéric; Bousiges, Olivier; Wahlund, Lars-Olof; Pilotto, Andrea; Padovani, Alessandro; Boada, Mercè; Pagonabarraga, Javier; Kulisevsky, Jaime; Aarsland, Dag; Lemstra, Afina W.; Westman, Eric (Peer reviewed; Journal article, 2022)
      Background Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer’s disease (AD) and cerebrovascular pathologies are common in DLB. All this ...

    • Prediction of Psychosis in Parkinson’s Patients using Machine Learning 

      Podhraški, Andrijana; Tjersland, Trond (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 ...

    • Prostate Lesion Detection on Apparent Diffusion Coefficient MRI based on Convolutional Neural Networks 

      Obrestad, Emil (Master thesis, 2021)
      In 2020 there were 1 414 259 new incidences and 375 304 deaths worldwide caused by prostate cancer. The number of cases could increase even further in the future due to higher life expectancy and population growth. Prostate ...

    • A Randomised Placebo-Controlled Study of Purified Anthocyanins on Cognition in Individuals at Increased Risk for Dementia 

      Aarsland, Dag; Khalifa, Khadija; Bergland, Anne Katrine; Sønnesyn, Hogne; Oppedal, Ketil; Holteng, Lise Birgitte Austbø; Oesterhus, Ragnhild; Nakling, Arne; Jarholm, Jonas Alexander; de Lucia, Chiara; Fladby, Tormod; Brooker, Helen; Dalen, Ingvild; Ballard, Clive (Peer reviewed; Journal article, 2022)
      Importance Identifying nutritional compounds which can reduce cognitive decline in older people is a hugely important topic. Objective To study the safety and effect of anthocyanins in maintaining cognitive functioning ...

    • The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study 

      Mårtensson, Gustav; Ferreira, Daniel; Granberg, Tobias; Cavallin, Lena; Oppedal, Ketil; Padovani, Alessandro; Rektorova, Irena; Bonanni, Laura (Peer reviewed; Journal article, 2020-12)
      Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on ...