• Jump to content
  • Jump to navigation
  • Jump to bottom of page
Simulate organization breadcrumb open Simulate organization breadcrumb close
Pattern Recognition Lab
  • FAUTo the central FAU website
  • Campo
  • UnivIS
  • Jobs
  • Map
  • Help

Pattern Recognition Lab

Navigation Navigation close
  • Overview
    • Contact
    • Directions
    Portal Overview
  • Team
    • Former PRL members
    Portal Team
  • Research
    • Research Groups
    • Research Projects
    • Pattern Recognition Blog
    • Beyond the Patterns
    • Publications
    • Research Demo Videos
    • Datasets
    • Competitions
    Portal Research
  • Teaching
    • Curriculum / Courses
    • Lecture Notes
    • Lecture Videos
    • Thesis / Projects
    • Free Machine and Deep Learning Resources
    • Free Medical Engineering Resources
    • LME Videos
    Portal Teaching
  • Lab
    • News
    • Ph.D. Gallery
    • Cooperations
    • Join the Pattern Recognition Lab
    Portal Lab
  1. Home
  2. Research
  3. Research Groups
  4. Computer Vision
  5. Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

In page navigation: Research
  • Beyond the Patterns
  • Competitions
  • Publications
  • Datasets

Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

(Third Party Funds Single)

Overall project:
Project leader: Andreas Maier, Björn Eskofier
Project members: Jennifer Maier, Julia Schottenhamml, Prathmesh Madhu, Rebecca Fahrig, Peter Blank
Start date: June 1, 2018
End date: May 31, 2021
Acronym: Ait4Surgery
Funding source: Bundesministerium für Bildung und Forschung (BMBF)
URL:

Abstract

The goal of this project is the investigation of multimodal methods for the evaluation of interventional workflows in the operation room. This topic will be researched in an international project context with partners in Germany and in Brazil (UNISINOS in Porto Alegre). Methods will be developed to analyze the processes in an OR based on signals from body-worn sensors, cameras and other modalities like X-ray images recorded during the surgeries. For data analysis, techniques from the field of computer vision, machine learning and pattern recognition will be applied. The system will be integrated in a way that body-worn sensors developed by Portabiles as well as angiography systems produced by Siemens Healthcare can be included alongside.

Publications

  • Maier J., Schottenhamml J., Madhu P., da Costa CA., Maier A.:
    Analysis of Interventional Workflow Phases based on Image Classification
    65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) (Berlin (online conference), September 6, 2020 - September 9, 2020)
    In: 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) 2021
    DOI: 10.3205/20gmds187
    URL: https://www.egms.de/static/en/meetings/gmds2020/20gmds187.shtml
    BibTeX: Download
Friedrich-Alexander-Universität
Erlangen-Nürnberg

Schlossplatz 4
91054 Erlangen
  • Login
  • Intranet
  • Imprint
  • Privacy
  • Accessibility
Up