Biological dosimetry is crucial for estimating the doses from biological samples and guiding medical interventions for accidental radiation exposure. This study aimed to derive rapid and precise dose estimates using a dicentric chromosome assay. To address the challenges of manual scoring of dicentric chromosomes, we upgraded an automatic system aimed at enhancing the precision of dicentric chromosome detection while reducing the need for human intervention. We collected blood from 30 individuals aged 20–67 years to create 30 dose-response curves aiming to investigate the differences in responses among individuals. To validate dose-estimate accuracy within a 95% confidence interval, blinded samples were categorized into three groups according to the radiation dose as follows: ≥2, ≤ 1, and 0.1 Gy. When scoring dicentric chromosomes without human review and constructing a dose–response curve, individual differences were observed. For doses ≤ 1 Gy, the standard root formula was effective; conversely, for doses ≥ 2 Gy, the regression deep neural network proved to be more ac-curate. Our developed program allowed for the rapid analysis of a large volume of dicentric chromosome images.