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NILS - Neuroimaging Intelligent Linked System

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A comprehensive system for DICOM classification, sorting, anonymization, and BIDS export

Developed at Karolinska Institutet
Department of Clinical Neuroscience, Neuroradiology


What is NILS?

NILS (Neuroimaging Intelligent Linked System) is a full-stack application designed for research institutions to efficiently manage neuroimaging data. It provides a complete pipeline from raw DICOM ingestion to BIDS-compliant export.

Core Capabilities

Six-Axis Classification System

NILS classifies MRI series using six orthogonal axes:

Axis Description Examples
Base Contrast weighting T1w, T2w, PD, DWI, BOLD, SWI
Technique Pulse sequence family MPRAGE, TSE, FLASH, EPI, GRASE
Modifier Acquisition enhancements FLAIR, FatSat, MT, IR, PhaseContrast
Construct Derived/map type ADC, FA, MD, T1Map, T2Map, CBF
Provenance Processing pipeline SyMRI, SWIRecon, DTIRecon, RawRecon
Acceleration Parallel imaging GRAPPA, SMS, CAIPIRINHA

Data Hierarchy

NILS organizes imaging data in a 4-level hierarchy:

Subject (Patient)
└── Study (Imaging Session)
    └── Series (Acquisition)
        └── SeriesStack (Homogeneous Instance Group)

SeriesStack is a key concept - it represents a group of instances within a series that share identical acquisition parameters. This handles multi-echo, multi-flip-angle, and other complex acquisitions.

Documentation

Quick Start

# Clone and start
git clone https://github.com/NeuroGranberg/NILS.git
cd NILS
./scripts/manage.sh start

# Access web interface
open http://localhost:5173

Requirements

  • Docker & Docker Compose
  • 4GB RAM minimum (8GB recommended)
  • Modern web browser

License

MIT License - See LICENSE

Citation

If you use NILS in your research, please cite:

Chamyani, N. (2025). NILS - Neuroimaging Intelligent Linked System. Karolinska Institutet, Department of Clinical Neuroscience. https://github.com/NeuroGranberg/NILS