Abstract
Advances in imaging techniques have yielded massive images into the biology. Along with the increase of dimension and data size of bioimages in the research field, a need for computer-aided image analysis becomes clear. However, software environments are not utilized enough for image analysis. This is because the versatility of purposes and the diversity of bioimages. In this review, approaches for development of bioimage classifiers are outlined as follows: unsupervised learning, supervised learning and active learning. We have developed an adaptive classification system for bioimages, named "clustering-aided rapid training agent (CARTA)". The CARTA is applicable to various bioimage classification that facilitates annotation and selection of features. The CARTA interactively collects information from experts and generates the customized classifier for the specified bioimages.
