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You Only Look Once (YOLO)-based object detectors have shown remarkableaccuracy for automated brain tumor detection. In this paper, we develop a novelBGF-YOLO architecture by incorporating Bi-level Routing Attention (BRA),Generalized feature pyramid networks (GFPN), and Fourth detecting head intoYOLOv8. BGF-YOLO contains an attention mechanism to focus more on importantfeatures, and feature pyramid networks to enrich feature representation bymerging high-level semantic features with spatial details. Furthermore, weinvestigate the effect of different attention mechanisms and feature fusions,detection head architectures on brain tumor detection accuracy. Experimentalresults show that BGF-YOLO gives a 4.7% absolute increase of mAP$_{50}$compared to YOLOv8x, and achieves state-of-the-art on the brain tumor detectiondataset Br35H. The code is available at https://github.com/mkang315/BGF-YOLO.

BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection