基于深度学习的神经母细胞瘤计算机辅助分级系统的研发初探

Development of a Deep Learning Algorithm for Classification of Neuroblastoma

摘要: 该文拟以深度学习（Deep Learning）为核心技术，采用卷积神经网络（Convolutional Neural Network，CNN）算法构建不同的分类器，实现磁共振图像中神经母细胞瘤的分类和定位，并将模块进行集成实现计算机辅助诊断软件的开发，用以弥补目前磁共振检测技术在神经母细胞瘤智能识别和精准定位这一领域的空白，有效降低医生读片的工作强度，进一步促进磁共振检测技术在神经母细胞瘤诊断方面的临床应用和技术发展。

Abstract: In this paper, the classification and location of neuroblastoma in NMR images are realized by using Deep Neural Network(CNN) algorithm as the core technology. The module is integrated to realize the development of computer-aided diagnostic software. It is used to make up for the gap in the field of intelligent identification and accurate positioning of neuroblastoma in the current nuclear magnetic resonance detection technology, effectively reduce the work intensity of doctors reading films, and further promote the clinical application and technical development of nuclear magnetic resonance detection technology in the diagnosis of neuroblastoma.