| Title | Development of a Next-Generation Automated DICOM Processing System in a PACS-Less Research Environment. |
| Publication Type | Journal Article |
| Year of Publication | 2012 |
| Authors | Ziegler, SE |
| Journal | J Digit Imaging |
| Date Published | 2012 May 1 |
| ISSN | 1618-727X |
| Abstract | The use of clinical imaging modalities within the pharmaceutical research space provides value and challenges. Typical clinical settings will utilize a Picture Archive and Communication System (PACS) to transmit and manage Digital Imaging and Communications in Medicine (DICOM) images generated by clinical imaging systems. However, a PACS is complex and provides many features that are not required within a research setting, making it difficult to generate a business case and determine the return on investment. We have developed a next-generation DICOM processing system using open-source software, commodity server hardware such as Apple Xserve®, high-performance network-attached storage (NAS), and in-house-developed preprocessing programs. DICOM-transmitted files are arranged in a flat file folder hierarchy easily accessible via our downstream analysis tools and a standard file browser. This next-generation system had a minimal construction cost due to the reuse of all the components from our first-generation system with the addition of a second server for a few thousand dollars. Performance metrics were gathered and the system was found to be highly scalable, performed significantly better than the first-generation system, is modular, has satisfactory image integrity, and is easier to maintain than the first-generation system. The resulting system is also portable across platforms and utilizes minimal hardware resources, allowing for easier upgrades and migration to smaller form factors at the hardware end-of-life. This system has been in production successfully for 8 months and services five clinical instruments and three pre-clinical instruments. This system has provided us with the necessary DICOM C-Store functionality, eliminating the need for a clinical PACS for day-to-day image processing. |
| DOI | 10.1007/s10278-012-9482-6 |
| PubMed ID | 22546983 |
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