Techniques for Image Analysis to Automated Diagnosis

The advent of digital pathology is still far from replacing trained pathologists. However, in order to continue the trend from image analysis to automated diagnosis it is essential to have standardization procedures in acquiring information from a digitized slide. Engineers must create algorithms that assess images with diagnostic value as a pathologist would. For artificial intelligent imaging systems, the important parameters are discussed below:

1. Image Standardization-a number of factors contribute to glass slide variations including but not limited to thickness of the cuts and staining intensity. These factors must be corrected during the information extraction phase from the virtual slide.


2. Selection of Segmentation Thresholds-images must be pre-analyzed to select useful object segmentation.


3. Segmentation Algorithms-object and structure information require accurate magnification which can be achieved with appropriate segmentation algorithms. Algorithms involve choosing a simple gray value to determine the object space and the application of a number of algorithms to identify object boundaries.


4. Sampling Algorithms of Field of View-fields of view that are diagnostically significant must be chosen with well structured sampling methods which may include self-adjusting segmentation procedures or implementations in distributed manners.


5. Texture Analysis-information such as translation figures, image entropy, and symmetries can be extracted from pixel-based images using texture analysis algorithms. Here texture is a pixel based gray value that is independent of external setups. It involves image transformations such as Fourier, Hough, and Hadamard methods. Texture analyses have been used in classifying lung cancer cell types and cancer cell types of various origins.


6. Structure Analysis-the spatial position of objects is necessary to extract feature measurements. This requires a mathematical procedure and a neighborhood condition where graph theory is often applied for analyses. Structure analysis is related to symmetry operations in pathology to contrast between normal glandular organs and cancer.


7. Statistical Analysis-analysis of quantified parameters and classification schemes must be performed to generate automated diagnosis.


8. Continuous Improvement of Classification Procedures-results should be monitored and re-evaluated, in which classification procedures are readjusted if necessary.