Fig. 1.

Summary of the convolutional network architecture within YoloV3. This network extracts latent features via repeated convolutional and residual layers, and aggregates learned features via a fully connected block to make two sets of predictions: (1) rectangular bounding boxes that circumscribe potential free fluid regions, and (2) the confidence score in the range [0,1] that is associated with each free fluid detection. Each FAST exam is analyzed image-by-image and free fluid presence in the exam is determined from the most confident detection