An image analysis method for prostate tissue classification : preliminary validation with resonance sensor data

• 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 (R(2) = 0.68, n = 109, p < 0.001) and partial least squares (R(2) = 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%.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik -- Medicinsk laboratorie- och mätteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering -- Medical Laboratory and Measurements Technologies (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik -- Annan medicinteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering -- Other Medical Engineering (hsv//eng)

Nyckelord

Image analysis

prostate tissue

classification

resonance sensor

Medical engineering

Medicinsk teknik

fysik

Physics

Medical Engineering for Healthcare

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