From the author
Use this skill whenever the user wants to convert DICOM files or folders to NIfTI format (.nii or .nii.gz), extract neuroimaging volumes from clinical DICOM series (MRI, CT, PET, etc.), prepare raw DICOM data for research processing pipelines, anonymize while converting, or batch-convert multiple series/studies. Triggers include: 'DICOM to NIfTI', 'dcm to nii', 'convert dicom to nii.gz', 'dcm2niix', 'extract nii from dicom', 'batch dicom to nifti', 'prepare dicom for freesurfer/fsl/spm', 'anonymized nifti conversion', or any request to transform clinical DICOM data into analysis-ready NIfTI format while preserving orientation, voxel spacing, slice timing (when available), and important metadata in the JSON sidecar.
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill dcm2nii -a claude-code
Installs to .claude/skills/dcm2nii/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (Custom or unclear) does not let us redistribute its files. The install commands fetch them from GitHub instead.
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Why 74
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- nii2dcmBioTender-max/awesome-bio-agent-skillsUse this skill whenever the user wants to convert NIfTI files (.nii or .nii.gz) to DICOM format, create DICOM series from processed neuroimaging results, write segmentation/registration/analysis outputs back to DICOM for PACS compatibility or clinical viewer comparison, or transfer metadata from reference DICOM files. Triggers include: mentions of 'NIfTI to DICOM', 'nii to dcm', 'convert nii.gz to DICOM', 'dicomify segmentation', 'nii2dcm', 'bring results back to DICOM', 'create DICOM from NIfTI', 'nii to dicom series', or any request to take post-processed neuroimaging results (segmentation, registration, bias field correction, synthesis, etc.) and store/view them alongside original patient DICOM data. Also use when modality-specific metadata (especially MR, SVR) or preservation of patient/study information from a reference DICOM is needed. Do NOT use for the reverse conversion (DICOM to NIfTI), non-medical imaging file conversions, or any clinical diagnostic or treatment-related workflows.Science★ 206
- dicom-processingawslabs/hcls-agent-skillsDICOM and NIfTI medical image processing pipeline. Triggers on DICOM, NIfTI, dcm2niix, de-identification, pydicom, DICOM header, conversion, anonymization, BIDS, DICOM tags, medical image format conversion, "DICOM to NIfTI", "burned-in PHI", "SeriesInstanceUID", "nibabel", "DICOM anonymization".Media★ 66
- imaging-dataAperivue/medsci-skillsUse when preparing a medical-imaging dataset (DICOM/NIfTI) for modelling. Profiles spacing, orientation, intensity, label integrity, foreground fraction and target volume, gates them against the plan, then plans and audits preprocessing and augmentation for leakage.Science★ 349
- pydicomK-Dense-AI/scientific-agent-skillsReads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.Writing★ 54.5K
- dicom-series-to-volumeNVIDIA/skillsUsed for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.Science★ 3.7K
- pydicom-medical-imagingjaechang-hits/SciAgent-SkillsPure Python DICOM for medical imaging (CT, MRI, X-ray, ultrasound). Read/write DICOM, pixels as NumPy, edit tags, windowing (VOI LUT), PHI anonymization, build DICOM, series→3D volumes. Use histolab for WSI pathology; nibabel for NIfTI.Science★ 383
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