抄録
In this paper, linear subspaces are used for detecting and retrieving rare cells called nucleated red blood cells (NRBCs) from microscope images. In our method, NRBCs are detected based on similarities between a candidate region and two subspaces spanned by NRBC images and their similar ones. After that, detected NRBC candidates are displayed to users in ascending order of the dissimilarities defined by the difference of similarities to each subspace. Furthermore, we derive a learning rule for our method for improving detection performance. Experimental results show that our method can detect NRBCs in about one second per microscope image and our learning can reduce the number of false detection.
