Advancing Image Database Technologies in Clinical Decision Support Systems: A Systematic Literature Review

Image data has played a crucial role in the Clinical Decision Support System (CDSS). While numerous studies have focused on developing techniques to extract valuable information from image data to aid in disease diagnosis, there is a lack of attention on the storage and retrieval technologies for image database. Extracting information from image data for decision making models requires a substantial volume of image data. However, images often come with large file sizes due to their high resolution and complex details, and compressing such data may lead to the loss of critical diagnostic information. Thus, the challenge lies in preserving the relevant information within images while managing data volume. This literature review aims to explore existing research on image-specific database systems, and their techniques for image data storage and information retrieval to enhance the application of images within CDSS. The review also brings attention to the need for specialized database systems that are tailored to handle the unique characteristics of clinical image data. Consequently, this review serves as a foundation for future research endeavors aimed at advancing image data management and utilization in the realm of medical diagnosis and beyond.