LOUKAS, CONSTANTINOS G.;
WILSON, GEORGE D.;
VOJNOVIC, BORIVOJ;
LINNEY, ALF
Tumor Hypoxia and Blood Vessel Detection : An Image Analysis Technique for Simultaneous Tumor Hypoxia Grading and Blood Vessel Detection in Tissue Sections
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Medientyp:
E-Artikel
Titel:
Tumor Hypoxia and Blood Vessel Detection : An Image Analysis Technique for Simultaneous Tumor Hypoxia Grading and Blood Vessel Detection in Tissue Sections
:
An Image Analysis Technique for Simultaneous Tumor Hypoxia Grading and Blood Vessel Detection in Tissue Sections
Beschreibung:
<jats:p><jats:bold>A<jats:sc>bstract</jats:sc>: </jats:bold> We have developed a multistage image analysis technique for the simultaneous segmentation of blood vessels and hypoxic regions in dual‐stained tumor tissue sections. The algorithm, which is integrated in a task‐oriented image analysis system developed on‐site, initially uses the <jats:italic>K</jats:italic>‐nearest neighbor classification rule in order to label the image pixels. Classification is based on a training set selected from manually drawn regions corresponding to the areas of interest. If the output image contains a significant number of misclassified pixels, the user has the option to apply a series of specific problem‐designed routines (texture analysis, fuzzy <jats:italic>c</jats:italic>‐means clustering, and edge detection) in order to improve the final segmentation result. Validation experiments indicate that the algorithm can robustly detect these biological features, even in tissue sections with a very low quality of staining. This approach has also been combined with other image analysis based procedures in order to objectively obtain quantitative measurements of potential clinical interest.</jats:p>