  Radiomics is a promising technology that focuses on improvements of image
analysis, using an automated high-throughput extraction of quantitative
features. However, the character of lesion is affected by the surrounding
tissue. A lesion on medical image should be characterized from the
inter-relation between lesion and surrounding tissue as well as property of the
lesion itself. The aim of this study is to introduce a new radiomics feature
which quantitatively analyze the inter-relation between lesion and surrounding
tissue focusing on the value change of rows and columns in a medical image.
