17 citations · 21 across the 6 of their papers we have counts for
6 papers
Artificial Intelligence-Assisted Prostate Cancer Diagnosis for Reduced Use of Immunohistochemistry
Anders Blilie, Nita Mulliqi, Xiaoyi Ji +13
Prostate cancer diagnosis heavily relies on histopathological evaluation, which is subject to variability. While immunohistochemical staining (IHC) assists in distinguishing benign…
The impact of tissue detection on diagnostic artificial intelligence algorithms in digital pathology
Sol Erika Boman, Nita Mulliqi, Anders Blilie +18
Tissue detection is a crucial first step in most digital pathology applications. Details of the segmentation algorithm are rarely reported, and there is a lack of studies investiga…
Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education
Neel Kanwal, Emiel A. M. Janssen, Kjersti Engan
The advancement of biomedical research heavily relies on access to large amounts of medical data. In the case of histopathology, Whole Slide Images (WSI) and clinicopathological in…
Deep Learning for Predicting Metastasis on Melanoma WSIs
Christopher Andreassen, Saul Fuster, Helga Hardardottir +2
Northern Europe has the second highest mortality rate of melanoma globally. In 2020, the mortality rate of melanoma rose to 1.9 per 100 000 habitants. Melanoma prognosis is based o…
Detection and Localization of Melanoma Skin Cancer in Histopathological Whole Slide Images
Neel Kanwal, Roger Amundsen, Helga Hardardottir +4
Melanoma diagnosed and treated in its early stages can increase the survival rate. A projected increase in skin cancer incidents and a dearth of dermatopathologists have emphasized…
Challenging mitosis detection algorithms: Global labels allow centroid localization
Claudio Fernandez-Martín, Umay Kiraz, Julio Silva-Rodríguez +3
Mitotic activity is a crucial proliferation biomarker for the diagnosis and prognosis of different types of cancers. Nevertheless, mitosis counting is a cumbersome process for path…