Skip to main content

Neuro-SAM: Foundation Models for Dendrite and Dendritic Spine Segmentation

Project description

Neuro-SAM

Foundation Model from Dendrite and Dendritic Spine Segmentation

Neuro-SAM enables you to:

  • Trace individual dendrite in a 3D stack
  • Segment traced dendrites using fine-tuned SAMv2
  • Tubular View Analysis of the dendrites
  • Segment Dendritic Spines using our custom model

Neuro-SAM works across different imaging modalities including two-photon, confocal and STED microscopy.

🚀 Installation

Neuro-SAM requires Python 3.10+ installed on your machine. It is recommended to use Conda/Miniconda for environment management. You can also use CUDA for GPU based accelerations. Our model are also optimised to use MPS on Apple Silicon (M series chips).

To install Neuro-SAM:

pip install neuro-sam

Downloading models and sample dataset

neuro-sam-download

📊 Usage

# base usage with benchmark dataset
neuro-sam

# using with your own dataset
neuro-sam --image-path /path/to/your/image.tif

🔬 Workflow

1. Configure Voxel Spacing

Set accurate X, Y, Z voxel spacing in the "Path Tracing" tab for proper scaling:

2. Trace Dendritic Paths

  • Click waypoints along dendrite structures
  • Algorithm automatically finds optimal brightest paths

3. Segment Dendrites

  • Load pre-trained SAMv2 dendrite model
  • Segment individual path with SAMv2

4. Segment Spines

  • Segment Dendritic Spines with our fine tuned model

📬 Contact

Made with ♥️ at Anki Lab 🧠✨

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neuro_sam-0.1.15.tar.gz (190.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

neuro_sam-0.1.15-py3-none-any.whl (250.7 kB view details)

Uploaded Python 3

File details

Details for the file neuro_sam-0.1.15.tar.gz.

File metadata

  • Download URL: neuro_sam-0.1.15.tar.gz
  • Upload date:
  • Size: 190.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for neuro_sam-0.1.15.tar.gz
Algorithm Hash digest
SHA256 7d8ae38711ebeffcee1748f806445d4cb3ff95e954dba7dbeba014411bad63b0
MD5 8f9eefb4705c4a0f1fc40bc24e8142f0
BLAKE2b-256 362d97e4f1b9ba10ae1b80c64c1d4ed9e9aa40a7f11f3a17a2e295844454b23f

See more details on using hashes here.

File details

Details for the file neuro_sam-0.1.15-py3-none-any.whl.

File metadata

  • Download URL: neuro_sam-0.1.15-py3-none-any.whl
  • Upload date:
  • Size: 250.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for neuro_sam-0.1.15-py3-none-any.whl
Algorithm Hash digest
SHA256 19aae05d3e703d8c2635ef1a87d0ba925bf349f7c049610bd42b0dd7c6dd361e
MD5 c9e2494007a0775546ae7be23c05f93d
BLAKE2b-256 8ccb6873968ce6041968696d98d6a6f84e607f986e77357e6a941891ae0c3f68

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page