Procedurally Generated Colonoscopy and Laparoscopy Data For Improved Model Training Performance

DOI

This is the training data to support the work in 'Procedurally Generated Colonoscopy and Laparoscopy Data For Improved Model Training Performance', published at the 2023 Data Engineering in Medical Imaging Workshop at MICCAI 2023.

Contents:

  1. blender.zip - Blender files used to generate data.
  2. examples.zip - Example videos showing Shader Graphs, Geometry Nodes and data generation.
  3. liver.zip - The full generated laparoscopy dataset.
  4. colon.zip - The full generated colonoscopy dataset.
Identifier
DOI https://doi.org/10.5522/04/23843904.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/41833146
Related Identifier HasPart https://ndownloader.figshare.com/files/41835510
Related Identifier HasPart https://ndownloader.figshare.com/files/41835753
Related Identifier HasPart https://ndownloader.figshare.com/files/41838570
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/23843904
Provenance
Creator Dowrick, Thomas; Clarkson, Matt; Ramalhinho, Joao; Chen, Long; Gonzalez Bueno Puyal, Juana
Publisher University College London UCL
Contributor Figshare
Publication Year 2023
Rights https://creativecommons.org/publicdomain/zero/1.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences; Natural Sciences; Physics