liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Asa, Sylvia
    et al.
    Department of Pathology, University Health Network, Toronto, Ontario, Canada.
    Bodén, Anna
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Treanor, Darren
    University of Leeds, and Leeds Teaching Hospitals NHS Trust Leeds, UK.
    Jarkman, Sofia
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Lundström, Claes
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Pantatnowitz, Liron
    Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, USA.
    2020 vision of digital pathology in action2019In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 10, no 27Article in journal (Other academic)
  • 2.
    Capitanio, Arrigo
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Dina, R. E.
    Imperial Coll NHS Trust, England.
    Treanor, Darren
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology. Leeds Teaching Hosp NHS Trust, England.
    Digital cytology: A short review of technical and methodological approaches and applications2018In: Cytopathology, ISSN 0956-5507, E-ISSN 1365-2303, Vol. 29, no 4, p. 317-325Article, review/survey (Refereed)
    Abstract [en]

    The recent years have been characterised by a rapid development of whole slide imaging (WSI) especially in its applications to histology. The application of WSI technology to cytology is less common because of technological problems related to the three-dimensional nature of cytology preparations (which requires capturing of z-stack information, with an increase in file size and usability issues in viewing cytological preparations). The aim of this study is to provide a review of the literature on the use of digital cytology and provide an overview of cytological applications of WSI in current practice as well as identifying areas for future development.

  • 3.
    Falk, Martin
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Ynnerman, Anders
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Treanor, Darren
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Leeds Teaching Hospitals NHS Trust, United Kingdom.
    Lundström, Claes
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linköping, Sweden.
    Interactive Visualization of 3D Histopathology in Native Resolution2019In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 25, no 1, p. 1008-1017Article in journal (Refereed)
    Abstract [en]

    We present a visualization application that enables effective interactive visual analysis of large-scale 3D histopathology, that is, high-resolution 3D microscopy data of human tissue. Clinical work flows and research based on pathology have, until now, largely been dominated by 2D imaging. As we will show in the paper, studying volumetric histology data will open up novel and useful opportunities for both research and clinical practice. Our starting point is the current lack of appropriate visualization tools in histopathology, which has been a limiting factor in the uptake of digital pathology. Visualization of 3D histology data does pose difficult challenges in several aspects. The full-color datasets are dense and large in scale, on the order of 100,000 x 100,000 x 100 voxels. This entails serious demands on both rendering performance and user experience design. Despite this, our developed application supports interactive study of 3D histology datasets at native resolution. Our application is based on tailoring and tuning of existing methods, system integration work, as well as a careful study of domain specific demands emanating from a close participatory design process with domain experts as team members. Results from a user evaluation employing the tool demonstrate a strong agreement among the 14 participating pathologists that 3D histopathology will be a valuable and enabling tool for their work.

  • 4.
    Lundström, Claes
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering. Sectra AB.
    Thorstenson, Sten
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Waltersson, Marie
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Treanor, Darren
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. St. James University Hospital, Leeds, England.
    Summary of 2nd Nordic symposium on digital pathology2015In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 6Article in journal (Refereed)
    Abstract [en]

    Techniques for digital pathology are envisioned to provide great benefits in clinical practice, but experiences also show that solutions must be carefully crafted. The Nordic countries are far along the path toward the use of whole-slide imaging in clinical routine. The Nordic Symposium on Digital Pathology (NDP) was created to promote knowledge exchange in this area, between stakeholders in health care, industry, and academia. This article is a summary of the NDP 2014 symposium, including conclusions from a workshop on clinical adoption of digital pathology among the 144 attendees.

  • 5.
    Lundström, Claes
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Waltersson, Marie
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Treanor, Darren
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Department of Cellular Pathology, St. James University Hospital, Leeds, UK.
    Summary of third Nordic symposium on digital pathology2016In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 7, no 12Article in journal (Other academic)
    Abstract [en]

    Cross-disciplinary and cross-sectorial collaboration is a key success factor for turning the promise of digital pathology into actual clinical benefits. The Nordic symposium on digital pathology (NDP) was created to promote knowledge exchange in this area, among stakeholders in health care, industry, and academia. This article is a summary of the third NDP symposium in Linkφping, Sweden. The Nordic experiences, including several hospitals using whole-slide imaging for substantial parts of their primary reviews, formed a fertile base for discussions among the 190 NDP attendees originating from 15 different countries. This summary also contains results from a survey on adoption and validation aspects of clinical digital pathology use.

  • 6.
    Skoglund, Karin
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Divison of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
    Rose, Jeronimo
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lindvall, Martin
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra AB, Linköping, Sweden.
    Lundström, Claes
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra AB, Linköping, Sweden.
    Treanor, Darren
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Clinical pathology. St. James University Hospital, Leeds, UK.
    Annotations, ontologies, and whole slide images: Development of an annotated ontology-driven whole slide image library of normal and abnormal human tissue2019In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 10, no 22Article in journal (Refereed)
    Abstract [en]

    Objective: Digital pathology is today a widely used technology, and the digitalization of microscopic slides into whole slide images (WSIs) allows the use of machine learning algorithms as a tool in the diagnostic process. In recent years, “deep learning” algorithms for image analysis have been applied to digital pathology with great success. The training of these algorithms requires a large volume of high-quality images and image annotations. These large image collections are a potent source of information, and to use and share the information, standardization of the content through a consistent terminology is essential. The aim of this project was to develop a pilot dataset of exhaustive annotated WSI of normal and abnormal human tissue and link the annotations to appropriate ontological information. 

    Materials and Methods: Several biomedical ontologies and controlled vocabularies were investigated with the aim of selecting the most suitable ontology for this project. The selection criteria required an ontology that covered anatomical locations, histological subcompartments, histopathologic diagnoses, histopathologic terms, and generic terms such as normal, abnormal, and artifact. WSIs of normal and abnormal tissue from 50 colon resections and 69 skin excisions, diagnosed 2015-2016 at the Department of Clinical Pathology in Linköping, were randomly collected. These images were manually and exhaustively annotated at the level of major subcompartments, including normal or abnormal findings and artifacts. 

    Results: Systemized nomenclature of medicine clinical terms (SNOMED CT) was chosen, and the annotations were linked to its codes and terms. Two hundred WSI were collected and annotated, resulting in 17,497 annotations, covering a total area of 302.19 cm2, equivalent to 107,7 gigapixels. Ninety-five unique SNOMED CT codes were used. The time taken to annotate a WSI varied from 45 s to over 360 min, a total time of approximately 360 h. 

    Conclusion: This work resulted in a dataset of 200 exhaustive annotated WSIs of normal and abnormal tissue from the colon and skin, and it has informed plans to build a comprehensive library of annotated WSIs. SNOMED CT was found to be the best ontology for annotation labeling. This project also demonstrates the need for future development of annotation tools in order to make the annotation process more efficient.

1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf