An AC-SPCNN segmentation method for brain tumor images

In this paper, a brain tumor image segmentation method based on awareness-connected simplified pulse-coupled neural network (AC-SPCNN) is proposed. Accurate segmentation of brain tumors is crucial for diagnosis and treatment. Traditional segmentation methods usually rely on manual feature extraction and complex image processing techniques, which have limitations in dealing with complex medical images. The AC-SPCNN model proposed in this paper effectively improves the segmentation accuracy and robustness. The experimental results show that the method outperforms the existing state-of-the-art methods in several evaluation metrics and provides an effective solution for brain tumor image segmentation.