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LEARNING OUTCOMES
Upon successful completion of the course the student will be able:
• To be familiar with the design and operation of medical image analysis systems used in
Medicine (histopathological image analysis system, radiological image, biological image,
hematology, microscope images).
• To have knowledge of the methodologies for mathematical quantification of texture
properties, edge and other properties of the image (e.g. homogeneity textureinhomogeneity texture).
• To have knowledge of the methods of classification into categories (e.g. benign –
malignant cancer) of images based on the quantified properties of the medical image
(texture characteristics- features of 1st class, 2nd class, etc.).
• To have knowledge of the methods of evaluating the quality of medical image analysis
systems (Leave one out method- Exhaustive search).
Course aim:
Pattern Recognition System is a Decision Support System (DSS) that gives a possible diagnosis which is taken into account by the pathologist, in order to make the final diagnosis. With a command in the program, a series of elements from the image are collected (texture characteristics – a series of numbers that express the texture of the cell nucleus), on the basis of which a possible diagnosis of a degree of malignancy is made.
The analysis of medical images is important in extracting useful information, in describing and classifying them in the computer. Image analysis differs from other types of image
processing methods, such as restoration and quality optimization, as the final outcome is usually numerical rather than virtual. Consequently, image resolution is not concerned with
improving image quality. It deals with the diagnosis, in a similar way that the pathologist examines an image: The computer examines the image, detects and quantifies features and properties of the image and suggests a possible diagnosis (e.g. benign – malignant cancer). A medical image analysis system includes: Production of features that quantify medical image properties, system design with methods of classification and evaluation of system reliability.
Course objective:
The student can formulate with a mathematical approach the structure of the image analysis systems used in Medicine.
Course field:
The subject of Pattern Recognition briefly includes the following sections:
- Medical image analysis
- Data acquisition – Samples preparation
- Data processing
- Image resolution – Feature extraction
- Pattern Classification
- Integrated system design
- Methods of evaluation and reliability of the system