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An image analysis method for prostate tissue classification preliminary validation with resonance sensor data
Umeå University. Department of Applied Physics and Electronics.
Umeå University. Department of Applied Physics and Electronics.
Department of Medical Biosciences Pathology, Umeå University.
Department of Surgical and Preoperative Science, Urology and Andrology, Umeå University.
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2009 (English)In: Journal of Medical Engineering & Technology, ISSN 0309-1902, E-ISSN 1464-522X, Vol. 33, no 1, p. 18-24Article in journal (Refereed) Published
Abstract [en]

Resonance sensor systems have been shown to be able to distinguish between cancerous and normal prostate tissue, in vitro. The aim of this study was to improve the accuracy of the tissue determination, to simplify the tissue classification process with computerized morphometrical analysis, to decrease the risk of human errors, and to reduce the processing time. In this article we present our newly developed computerized classification method based on image analysis. In relation to earlier resonance sensor studies we increased the number of normal prostate tissue classes into stroma, epithelial tissue, lumen and stones. The linearity between the impression depth and tissue classes was calculated using multiple linear regression (R2 = 0.68, n = 109, p < 0.001) and partial least squares (R2 = 0.55, n = 109, p < 0.001). Thus it can be concluded that there existed a linear relationship between the impression depth and the tissue classes. The new image analysis method was easy to handle and decreased the classification time by 80%.

Place, publisher, year, edition, pages
2009. Vol. 33, no 1, p. 18-24
National Category
Other Medical Engineering
Research subject
Medical Engineering for Healthcare
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URN: urn:nbn:se:ltu:diva-8167DOI: 10.1080/03091900801945200Scopus ID: 2-s2.0-58149265072Local ID: 6a25bdf0-ed5e-11dd-8bf2-000ea68e967bOAI: oai:DiVA.org:ltu-8167DiVA, id: diva2:981058
Note

Validerad; 2009; 20090128 (olofl)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Lindahl, Olof

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