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
翻译:在技术开发中,脑疾病病例越来越多,有更多的治疗建议,并取得了积极的结果。然而,随着脑疏导,早期诊断可以改善成功治疗的可能性,有助于病人康复。从这个原因出发,脑疏导是当今医学图像分析中有争议的话题之一。随着结构的改进,提出了多种方法,提出了并取得了有竞争力的得分。在本文件中,我们提出了一种技术,即3D图像使用高效网,特别是用于脑疏导分类的高效网B0,并实现竞争性得分。此外,我们还提议了使用多尺度节能网络对MRI数据切片进行分类的方法。