Using computer vision to help the determination of the gestational age of newborns

Abstract

Rationale and objectives: This report presents a computational approach to help the gestational age determination of newborns. Gestational age knowledge is fundamental to guide postnatal treatment and increase survival chances of newborns. However, current methods are invasive and do not generate precise results, mainly because they were developed based on nonpremature populations.

Materials and methods: We developed an original and noninvasive method to help determination of gestational age based on information supplied by plantar surface images. These images present many details and patterns, but, to date, have not received attention from the image-processing community. We provide a computational tool with suitable facilities to allow the image analysis, either automatically or user driven. This image-processing tool is presented here.

Results: The image-processing tool was developed on a user-driven basis. However, as a quantitative experiment, 186 images were processed without user intervention to observe tool behavior in performing different tasks. Although preliminary, experimental results confirm the relationship between plantar surface features and gestational age.

Conclusion: A prototype of the FootScanAge System is being used and evaluated by experts in neonatology. By means of digital processing of plantar surface images, some characteristics may be shown. Some hypotheses regarding the method have already been confirmed. Also, we show that some well-known image-processing techniques, if appropriately adapted, lead to suitable results when applied to plantar surface images.