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Feature-enhancing zoom to facilitate Ki-67 hot spot detection
Linköping University, Center for Medical Image Science and Visualization (CMIV). Chalmers University of Technology, Gothenburg, Sweden.
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology. (MINT)ORCID iD: 0000-0002-0012-7867
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9368-0177
2014 (English)In: Medical Imaging 2014: Digital Pathology, SPIE - International Society for Optical Engineering, 2014, Vol. 9041, Art.nr. 90410W- p.Conference paper, Published paper (Refereed)
Abstract [en]

Image processing algorithms in pathology commonly include automated decision points such as classifications. While this enables efficient automation, there is also a risk that errors are induced. A different paradigm is to use image processing for enhancements without introducing explicit classifications. Such enhancements can help pathologists to increase efficiency without sacrificing accuracy. In our work, this paradigm has been applied to Ki-67 hot spot detection. Ki-67 scoring is a routine analysis to quantify the proliferation rate of tumor cells. Cell counting in the hot spot, the region of highest concentration of positive tumor cells, is a method increasingly used in clinical routine. An obstacle for this method is that while hot spot selection is a task suitable for low magnification, high magnification is needed to discern positive nuclei, thus the pathologist must perform many zooming operations. We propose to address this issue by an image processing method that increases the visibility of the positive nuclei at low magnification levels. This tool displays the modified version at low magnification, while gradually blending into the original image at high magnification. The tool was evaluated in a feasibility study with four pathologists targeting routine clinical use. In a task to compare hot spot concentrations, the average accuracy was 75±4.1% using the tool and 69±4.6% without it (n=4). Feedback on the system, gathered from an observer study, indicate that the pathologists found the tool useful and fitting in their existing diagnostic process. The pathologists judged the tool to be feasible for implementation in clinical routine.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2014. Vol. 9041, Art.nr. 90410W- p.
Series
Progress in Biomedical Optics and Imaging - Proceedings of SPIE, ISSN 1605-7422 ; 9041
Keyword [en]
cell nuclei; clinical evaluation; color deconvolution; zoom interaction
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-107494DOI: 10.1117/12.2043512ISI: 000337288300026Scopus ID: 2-s2.0-84901802123ISBN: 9780819498342 (print)OAI: oai:DiVA.org:liu-107494DiVA: diva2:724713
Conference
2nd Conference on Medical Imaging - Digital Pathology, San Diego, CA, USA, 16-17 Februari 2014
Funder
Swedish Research Council, 2011-4138VINNOVA, 2012-0112
Available from: 2014-06-13 Created: 2014-06-13 Last updated: 2017-02-03Bibliographically approved

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Shaga Devan, KavithaWårdell, KarinLundström, Claes

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Shaga Devan, KavithaWårdell, KarinLundström, Claes
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