支持多模态医学数据融合的并行加载算法

Parallel Loading Algorithm for Multimode Medical Data Fusion

由于多模态数据中的数据分属多种模态且相互之间存在互补关系,所以利用传统单模态数据的分析和处理方法无法有效地融合不同模态的数据并表示和处理不同模态数据之间的相互关系。为了解决多模态数据的建模、表示和存储问题,使得更好地融合不同模态的数据及更有效地表示数据之间的相互关系,本文提出了一种新的数据模型,即模态结构图,用于多模态医学数据的建模。该模型利用图结构对多模态数据中的模态及模态间的关系进行建模和表示。基于此模型,本文提出了一种并行的数据加载技术,用于抽取出多模态医学数据中分属不同模态和模态间关系的数据并存储到图数据库中。通过使用批量医学数据文件进行实验,验证了该提取加载技术能够获得较好的数据处理效率。

Since the different parts of multimode data belong to multiple modes and there are complementary relationships between them,the traditional analysis and processing techniques cannot fuse the data from different modes and their relationships.In order to solve the problems of modeling,representation and storage of multimode data,a new data model of modal structure graph is proposed to model the multimode medical data.The model utilizes the graph structure to model and represent the modes and their relationships in the multimode data.And based on the model,the paper proposes a parallel loading algorithm,which can extract the data of different modes and relationships,and store them in a graph database.Experimental results by using batch medical data files show that the proposed algorithm can obtain good data processing efficiency.