Abstract
Our group is developing prenatal DNA diagnosis with Nucleated Red Blood Cells (NRBC) of fetuses extracted from blood of their mothers. In this diagnosis, it is important to detect NRBC automatically from microscope images for efficient examining. In a research, an automatic NRBC detection system is proposed with two parts. The first part extracts candidate nucleuses with rule-based algorithm. The second part discriminates cell regions with machine learning algorithm. In the second part, Cell-HOG feature specialized for detecting NRBC is developed. Cell-HOG feature is customized HOG feature that emphasizes differences between NRBC and other cells such as white blood cells, out of focus cells, and red blood cells with foreign objects. By using Cell-HOG feature, number of false positives becomes to smaller than that of HOG feature.
