Morphometrical feature extraction on color histological images for oncological diagnostics

The diagnostics of oncological diseases is based on histological specimens in hematoxilin-eosin staining. Since manual evaluation of microscopy images is time consuming and depends on the human expert, several approaches to automatic image analysis and classification have been published. In such systems, feature extraction usually relies on a fixed resolution and a small number of numerical features. Contrarily, this framework is based on a morphometric study using two levels of optical magnification (50 and 200 times, correspondingly). In this paper, we propose a principle scheme for automation of the oncological diagnostics, and an algorithm of morphometric feature extraction of tissue fragment at low magnification. In particular, patterns of cells, vessels, and fragments of tissue are considered individually and combined for correct identification of objects extracted from the specimen. The fact of invasion is established automatically after this procedure as well as polymorphism, polychromism and anaplasia. Using this method, diagnostics of 86 out of 100 patients was confirmed.