Analysis of Histopathology Images by the Use of Monofractal and Multifractal Algorithms

The complexity of breast cancer histological images carries the information that could be useful in prognosis of metastatic occurrences. Computational tumour histomorphology analysis is a novel tool that aims to complement current prognostic approaches. This paper deals with the direct comparison of the prognostic value of different image formats and different image analysis algorithms. Generalizability of the methodology is investigated by the use of the two groups of patients. Binary and grayscale images of tumour histology samples from both patient groups were subjected to mono and multifractal analysis. On the basis of the obtained area under the curve values as a measure of feature's association with a disease outcome, it can be concluded that analysis of greyscale images delivered a far better performance in comparison to the analysis of binary images. Also, it should be noted that for different patient groups, algorithms were not equally successful which calls for further investigation.