Bone age assessment is an important clinical trial to measure skeletal child maturity and diagnose of growth disorders. Traditionalapproaches may not perform well due to their large inter-observer and intra-observer variations. Herewe propose a finger joint localization strategy to filter out most non-informative parts of images. When combining with the conventional full image-based deep network, we observe a muchimproved performanceusing our approach.