Neuroimaging Laboratory
University of Campinas
DBlni PACs
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DBlni Introduction
DBlni is a PACS (Picture Archiving and Communication System) developed at the Neuroimaging Laboratory to organize, index, and archive DICOM imaging data. The system is composed of two standalone applications:
1 - DBlniAdd: A data ingestion tool designed to import DICOM, NIfTI, and SPAR/SDAT files into the central repository while automatically extracting and updating metadata in the database. The software parses metadata from all files in a source directory, applies a standardized and user-friendly naming convention, and ensures structured, efficient archival of imaging datasets.
2 - DBlniFinder: The client interface for database querying and data retrieval. It provides a high-performance image search engine, supports file visualization through the DBlni Viewer, and allows direct downloading of selected datasets to user-defined local directories.
The software is cross-platform (Windows and macOS) and does not depend on proprietary or paid third-party libraries, facilitating deployment in research and clinical environments
DBlni Team
Coordinator and developer
Brunno M. de Campos, Ph.D.
DBlni Requirement
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Windows or Mac OS X operational system
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Matlab MRC (Included in the packing)
The DBlni has currently the following functionalities:
DBlni Finder:
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Smart Images search engine with 10 protocol/image filters
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Enable the creation of work groups of images for further download or visualisation.
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Enable the visualisation of 2D, 3D, or 4D DICOM, NIfTI and SPAR/SDAT files,
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Enable the direct downloading of images from the server to the local machine.
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The interface has three sub-tools:
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DICOM Renamer and Anonymizer
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Uncompress tool
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DICOM to NIfTI Converter (based on Chris Rhoerden's dcm2niix)
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DBlni Add
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Creates the database and the image repository
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Include new images to the database and repository from a source DICOM/NIfTI/SPAR-SDAT folder (external or internal disks or even network sources.
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The DICOM files are renamed to user-friendly filename format, and all data are compacted to increased storage capabilities.
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The images are stored in the repository with and smart and intuitive folder tree, aiming to a maximum speed to find and download. This is also relevant for backup or even manual access or managing of the data.
DBlni Add Interface example:
