论文标题
有效网络用于大脑质量分类
EfficientNet for Brain-Lesion classification
论文作者
论文摘要
在技术的发展中，脑部疾病的病例越来越多，提出了更多的治疗方法，并取得了积极的结果。但是，借助大脑质量，早期诊断可以改善成功治疗的可能性，并可以帮助患者更好地恢复治疗。源于这个原因，脑化是如今的医学图像分析中有争议的主题之一。随着体系结构的改善，提出了多种方法并获得竞争分数。在本文中，我们提出了一种技术，该技术将有效的网络用于3D图像，尤其是用于大脑质量分类任务解决方案的有效网络B0，并达到竞争分数。此外，我们还提出了使用多尺度效率网络对MRI数据切片进行分类的方法
In the development of technology, there are increasing cases of brain disease, there are more treatments proposed and achieved a positive result. However, with Brain-Lesion, the early diagnoses can improve the possibility for successful treatment and can help patients recuperate better. From this reason, Brain-Lesion is one of the controversial topics in medical images analysis nowadays. With the improvement of the architecture, there is a variety of methods that are proposed and achieve competitive scores. In this paper, we proposed a technique that uses efficient-net for 3D images, especially the Efficient-net B0 for Brain-Lesion classification task solution, and achieve the competitive score. Moreover, we also proposed the method to use Multiscale-EfficientNet to classify the slices of the MRI data
