Abstract
Mitotic count is helpful in determining the aggressiveness of breast cancer. In previous
studies, it was shown that the agreement among pathologists for grading mitotic index is fairly
modest, as mitoses have a large variety of appearances and they could be mistaken for other
similar objects. In this study, we determined local and contextual features that differ significantly
between easily identifiable mitoses and challenging ones. The images were obtained from the
Mitosis-Atypia 2014 challenge. In total, the dataset contained 453 mitotic figures. Two pathologists
annotated each mitotic figure. In case of disagreement, an opinion from a third pathologist was
requested. The mitoses were grouped into three categories, those recognized as “a true mitosis” by
both pathologists ,those labelled as “a true mitosis” by only one of the first two readers and also the
third pathologist, and those annotated as “probably a mitosis” by all readers or the majority of them.
After color unmixing, the mitoses were segmented from H channel. Shape-based features along
with intensity-based and textural features were extracted from H-channel, blue ratio channel and
five different color spaces. Holistic features describing each image were also considered. The
Kruskal-Wallis H test was used to identify significantly different features. Multiple comparisons
were done using the rank-based version of Tukey-Kramer test. The results indicated that there are
local and global features which differ significantly among different groups. In addition, variations
between mitoses in different groups were captured in the features from HSL and LCH color space
more than other ones.
