Abstract
We present new algorithms for the recognition of morphologic changes and shape feature analysis, which have been proposed to be used in a diagnosis of pathologic symptoms characteristic of cancerous and inflammatory lesions. These methods have been used so far for early detection and diagnosis of neoplastic changes in pancreas and chronic pancreatitis based on x-ray images acquired by endoscopic retrograde cholangiopancreatography (ERCP). Preliminary processing of x-ray images involves binarization, and, subsequently, pancreatic ducts shown in the pictures are subjected to the straightening transformation, which enables obtaining two-dimensional width graphs that show contours of objects with their morphologic changes. Recognition of such changes was performed using attributed context-free grammars. Correct description and diagnosis of some symptoms (e.g., large cavitary projections) required two-dimensional analysis of width graphs. In such cases, languages of shape feature description with special multidirectional sinquad distribution were additionally applied.