Fig. 9From: Automatic detection on intracranial aneurysm from digital subtraction angiography with cascade convolutional neural networksThe architecture of region localization stage (RLS). In this figure, ‘\({\text{Conv}} f{\times }f, c, /s\)’ denoted convolutional layer with size of filters f, and number of channels c and strides s (default strides was 1). Noting that each Conv layer was followed by a BN and an activation layer of ReLU. ‘\(\text{Pool} f {\times } f, /s\)’ meant max pooling layer whose size of filters f and strides s. ‘\({\text{Up-sample}}, /r\)’ indicated nearest neighbor up-sampling with up-sampling rate r. ‘Anchor’ was anchor box which was utilized to predict the PCoA region. The first part was an input receiving a three-channel RGB image. The following feature extraction block was FPN with backbone of ResNet50. At last, the anchor boxes output the PCoA region of original input imageBack to article page