A sensorized modular training platform to reduce vascular damage in endovascular surgery.
Nikola FischerChristian MarziKatrin MeisenbacherAnna KisilenkoTornike DavitashviliMartin WagnerFranziska Mathis-UllrichPublished in: International journal of computer assisted radiology and surgery (2023)
We investigated an authentic patient-specific training platform with integrated sensor-based feedback functionality for individual skill training in endovascular surgery. The presented method for phantom manufacturing is easily applicable to arbitrary patient-individual imaging data. Further work shall address the implementation of smaller vessel branches, as well as real-time feedback and camera imaging for further improved training experience.
Keyphrases
- minimally invasive
- virtual reality
- high resolution
- coronary artery bypass
- high throughput
- healthcare
- computed tomography
- oxidative stress
- magnetic resonance imaging
- atrial fibrillation
- electronic health record
- mass spectrometry
- fluorescence imaging
- acute coronary syndrome
- convolutional neural network
- single cell
- data analysis
- artificial intelligence