Analysis of texture and objects in microscopic images

Background: Tissue based diagnosis or surgical diagnostic pathology undergoes significant changes and focuses on image content analysis in our days. Herein we describe and discuss new approaches of content image analysis and compare their applications, benefits and constraints. Theory: Any useful microscopic image contains information that can be evaluated and transferred into a tissue-based diagnosis. A correctly derived diagnosis depends upon the image information and the pathologist’s knowledge, i.e. his ability to recognize and transfer the image content information into clinical application. Thus, image information is related to external “disease” information, i.e. interpretation, and “pure” image content information, which the pathologist has to interpret. Application of external image information requires definition and separation of objects from the background, or segmentation procedures. Observer free image information is solely pixel based. It can be analyzed using different approaches, such as entropy measure, construction of image primitives and their spatial distribution, or image similarity operations. Our approach uses entropy calculations dependent upon all possible gray value thresholds in combination with syntactic analysis of pixel based image primitives. Implementation: