A benchmark for 2D foetal brain ultrasound analysis
This provides a resource for researchers in medical imaging to improve analysis of foetal brain development, though it is incremental as it builds on existing data collection methods.
The authors tackled the challenge of interpreting foetal brain ultrasound images by creating a benchmark dataset of 104 2D images from the 20th week of gestation, co-registered and annotated with landmark points, enabling development of segmentation and registration techniques.
Brain development involves a sequence of structural changes from early stages of the embryo until several months after birth. Currently, ultrasound is the established technique for screening due to its ability to acquire dynamic images in real-time without radiation and to its cost-efficiency. However, identifying abnormalities remains challenging due to the difficulty in interpreting foetal brain images. In this work we present a set of 104 2D foetal brain ultrasound images acquired during the 20th week of gestation that have been co-registered to a common space from a rough skull segmentation. The images are provided both on the original space and template space centred on the ellipses of all the subjects. Furthermore, the images have been annotated to highlight landmark points from structures of interest to analyse brain development. Both the final atlas template with probabilistic maps and the original images can be used to develop new segmentation techniques, test registration approaches for foetal brain ultrasound, extend our work to longitudinal datasets and to detect anomalies in new images.