Diffuse white matter abnormality (DWMA) is observed in 50-80% of very preterm infants at term-equivalent age. Despite autopsy studies showing correlation with neuropathology, the relationship of DWMA with long term neurodevelopmental impairments remains controversial. The controversy may be due to the qualitative nature of previous studies of DWMA, likely resulting in measurement error and perhaps contributing to the lack of association with neurodevelopmental impairments in some studies. In this study, we developed a deep learning approach to objectively and automatically segment DWMA regions on T2-weighted MRI images. The internal and external validations demonstrated very accurate and reproducible DWMA segmentation performance.