Skip to main content

Python Library to handle Input / Output conversion in Dicom <=> Convolutional Neural Network

Project description

library-DICOM

Install : pip install dicom-to-cnn

Features :

  • Description of Series content in a huge dataset of DICOM (output JSON descriptor for each series containings main DICOM tags).
  • Conversion Dicom to Nifti
  • PET : Conversion Bqml/Counts to SUV and SUL

Roadmap :

  • Read RTSS to generate Mask
  • Generate RTSS from Mask
  • PT / CT fusion in 4D array np array

#Maintainer : Salim Kanoun #Contributors : Thomas Trouillard, Wendy Revailler

To refactor :

  • conversion of a nifti mask to a ROI in a DICOM RTSTRUCT
  • ROI integration to an existing RTSTRUCT
  • generation empty RTSTRUCT from PET,CT or similar set of DICOM images

TODO :

  • conversion DICOM RTSTRUCT to mask in nifti format

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

dicom_to_cnn-0.70.tar.gz (41.8 kB view details)

Uploaded Source

File details

Details for the file dicom_to_cnn-0.70.tar.gz.

File metadata

  • Download URL: dicom_to_cnn-0.70.tar.gz
  • Upload date:
  • Size: 41.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.40.2 CPython/3.8.5

File hashes

Hashes for dicom_to_cnn-0.70.tar.gz
Algorithm Hash digest
SHA256 df775783ab20d5715fec0f05fdf4eff90e51d0e91cffaaf22213c64dbc851ebd
MD5 e1b500ae4e5e7a9b1150fa7ed0b2d280
BLAKE2b-256 c4c914f1a2423adaaa5e584b03197be9b9a88b42e29b7fbf98fa227d146e86b4

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