medical-image-segmentation

Here are 3 public repositories matching this topic...

backblaze-b2-samples / nnunet-3d-medical-image-segmentation

Sample app for real nnU-Net 3D medical image segmentation: ingest CT/MRI NIfTI volumes, run nnunetv2 inference locally, and store every artifact — raw volumes, preprocessed tensors, masks, and the trained model checkpoint — on Backblaze B2 via the S3-compatible API. Next.js + FastAPI + PyTorch

deep-learning nextjs pytorch sample-app mri medical-imaging image-segmentation nifti object-storage backblaze-b2 cloudstorage medical-image-segmentation fastapi nnunet b2-labs

Updated Sep 11, 2026
TypeScript

backblaze-b2-samples / totalsegmentator-batch-pipeline

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Batch medical-imaging pipeline that ingests 3D CT/MRI volumes to Backblaze B2, runs TotalSegmentator locally to produce multi-label masks over 100+ anatomical structures plus per-structure volumetrics, and writes masks and stats back to B2. Next.js 16 + FastAPI sample app over the B2 S3-compatible API.

nextjs sample-app mri medical-imaging nifti batch-processing backblaze-b2 cloudstorage medical-image-segmentation fastapi ct-scan s3-compatible totalsegmentator b2-labs anatomy-segmentation

Updated Sep 16, 2026
TypeScript

backblaze-b2-samples / monai-dicom-segmentation

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Full-stack sample app that runs MONAI medical-image segmentation on DICOM/NIfTI volumes and stores the source scans, segmentation masks, and preview slices in Backblaze B2 via the S3-compatible API. Next.js 16 + FastAPI; models run on-device (CPU by default, GPU auto-detected).

python nextjs dicom pytorch medical-imaging image-segmentation nifti object-storage backblaze-b2 cloudstorage medical-image-segmentation fastapi monai b2-labs

Updated Sep 11, 2026
TypeScript

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