标题： SCC-YOLO：一种用于辅助脑肿瘤诊断的改进目标检测器 显示英文标题

标题： SCC-YOLO: An Improved Object Detector for Assisting in Brain Tumor Diagnosis

摘要： 脑肿瘤可能导致神经功能障碍、认知和心理变化、颅内压升高以及癫痫发作，对健康构成重大风险。 You Only Look Once（YOLO）系列在医学影像目标检测方面表现出卓越的准确性。 本文提出了一种新颖的SCC-YOLO架构，将SCConv模块集成到YOLOv9中。 SCConv模块通过减少空间和通道冗余来优化卷积效率，增强图像特征学习。 我们使用Br35H数据集和我们自定义的数据集（Brain_Tumor_Dataset），研究了与YOLOv9结合的不同注意力机制对脑肿瘤检测的影响。 结果显示，与YOLOv9相比，SCC-YOLO在Br35H数据集上的mAP50提高了0.3%，在我们的自定义数据集上提高了0.5%。 SCC-YOLO在脑肿瘤检测方面达到了最先进的性能。 显示英文摘要

摘要： Brain tumors can lead to neurological dysfunction, cognitive and psychological changes, increased intracranial pressure, and seizures, posing significant risks to health. The You Only Look Once (YOLO) series has shown superior accuracy in medical imaging object detection. This paper presents a novel SCC-YOLO architecture that integrates the SCConv module into YOLOv9. The SCConv module optimizes convolutional efficiency by reducing spatial and channel redundancy, enhancing image feature learning. We examine the effects of different attention mechanisms with YOLOv9 for brain tumor detection using the Br35H dataset and our custom dataset (Brain_Tumor_Dataset). Results indicate that SCC-YOLO improved mAP50 by 0.3% on the Br35H dataset and by 0.5% on our custom dataset compared to YOLOv9. SCC-YOLO achieves state-of-the-art performance in brain tumor detection.