Blar i forfatter "Johansen, Thomas Haugland"

Viser treff 1-6 av 6

    • Automatic detection of the mental foramen for estimating mandibular cortical width in dental panoramic radiographs: the seventh survey of the Tromsø Study (Tromsø7) in 2015-2016 

      Edvardsen, Isak Paasche; Teterina, Anna; Johansen, Thomas Haugland; Myhre, Jonas Nordhaug; Godtliebsen, Fred; Bolstad, Napat Limchaichana (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-11-22)
      Objective To apply deep learning to a data set of dental panoramic radiographs to detect the mental foramen for automatic assessment of the mandibular cortical width.<p> <p>Methods Data from the seventh survey of the Tromsø Study (Tromsø7) were used. The data set contained 5197 randomly chosen dental panoramic radiographs. Four pretrained object detectors were tested. We randomly chose 80% of the ...

    • Early Detection of Change by Applying Scale-Space Methodology to Hyperspectral Images 

      Uteng, Stig; Johansen, Thomas Haugland; Zaballos, Jose Ignacio; Ortega, Samuel; Holmström, Lasse; Callico, Gustavo M.; Fabelo, Himar; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-27)
      Given an object of interest that evolves in time, one often wants to detect possible changes in its properties. The first changes may be small and occur in different scales and it may be crucial to detect them as early as possible. Examples include identification of potentially malignant changes in skin moles or the gradual onset of food quality deterioration. Statistical scale-space methodologies ...

    • Instance Segmentation of Microscopic Foraminifera 

      Johansen, Thomas Haugland; Sørensen, Steffen Aagaard; Møllersen, Kajsa; Godtliebsen, Gustav (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-07-16)
      Foraminifera are single-celled marine organisms that construct shells that remain as fossils in the marine sediments. Classifying and counting these fossils are important in paleo-oceanographic and -climatological research. However, the identification and counting process has been performed manually since the 1800s and is laborious and time-consuming. In this work, we present a deep learning-based ...

    • Leveraging Computer Vision for Applications in Biomedicine and Geoscience 

      Johansen, Thomas Haugland (Doctoral thesis; Doktorgradsavhandling, 2021-06-25)
      Skin cancer is one of the most common types of cancer and is usually classified as either non-melanoma and melanoma skin cancer. Melanoma skin cancer accounts for about half of all skin cancer-related deaths. The 5-year survival rate is 99% when the cancer is detected early but drops to 25% once it becomes metastatic. In other words, the key to preventing death is early detection. Foraminifera ...

    • Recent advances in hyperspectral imaging for melanoma detection 

      Johansen, Thomas Haugland; Møllersen, Kajsa; Ortega, Samuel; Fabelo, Himar; Garcia, Aday; Callico, Gustavo; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-04-22)
      Skin cancer is one of the most common types of cancer. Skin cancers are classified as nonmelanoma and melanoma, with the first type being the most frequent and the second type being the most deadly. The key to effective treatment of skin cancer is early detection. With the recent increase of computational power, the number of algorithms to detect and classify skin lesions has increased. The overall ...

    • Towards detection and classification of microscopic foraminifera using transfer learning 

      Johansen, Thomas Haugland; Sørensen, Steffen Aagaard (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-02-06)
      <p>Foraminifera are single-celled marine organisms, which may have a planktic or benthic lifestyle. During their life cycle they construct shells consisting of one or more chambers, and these shells remain as fossils in marine sediments. Classifying and counting these fossils have become an important tool in e.g. oceanography and climatology. <p>Currently the process of identifying and counting ...