title: Multi-series DICOM: an extension of DICOM that stores a whole study in a single object.
abstract: Today, most medical images are stored as a set of single-frame composite Digital Imaging and Communications in Medicine (DICOM) objects that contain the four levels of the DICOM information model-patient, study, series, and instance. Although DICOM addresses most of the issues related to medical image archiving, it has some limitations. Replicating the header information with each DICOM object increases the study size and the parsing overhead. Multi-frame DICOM (MFD) was developed to address this, among other issues. The MFD combines all DICOM objects belonging to a series into a single DICOM object. Hence, the series-level attributes are normalized, and the amount of header data repetition is reduced. In this paper, multi-series DICOM (MSD) is introduced as a potential extension to the DICOM standard that allows faster parsing, transmission, and storage of studies. MSD extends the MFD de-duplication of series-level attributes to study-level attributes. A single DICOM object that stores the whole study is proposed. An efficient algorithm, called the one-pass de-duplication algorithm, was developed to find and eliminate the replicated data elements within the study. A group of experiments were done that evaluate MSD and the one-pass de-duplication algorithm performance. The experiments show that MSD significantly reduces the amount of data repetition and decreases the time required to read and parse DICOM studies. MSD is one possible solution that addresses the DICOM limitations regarding header information repetition.
authors: Department of Computer Science, Johns Hopkins University, 2933 N Charles st, Baltimore, MD 21218, USA. maismail@cs.jhu.edu
authors: Mahmoud
authors: M
authors: Ismail
authors: James
authors: J
authors: Philbin
mesh_terms: D000465:Algorithms; D003195:Computer Communication Networks; D001330:Electronic Data Processing / Q000379:methods*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D016347:Medical Records Systems, Computerized; D011873:Radiology Information Systems; D012984:Software