47 citations · 107 across the 8 of their papers we have counts for
9 papers
Surgical Phase and Instrument Recognition: How to identify appropriate Dataset Splits
Georgii Kostiuchik, Lalith Sharan, Benedikt Mayer +3
Purpose: Machine learning models can only be reliably evaluated if training, validation, and test data splits are representative and not affected by the absence of classes of inter…
Comparison of Depth Estimation Setups from Stereo Endoscopy and Optical Tracking for Point Measurements
Lukas Burger, Lalith Sharan, Samantha Fischer +7
To support minimally-invasive intraoperative mitral valve repair, quantitative measurements from the valve can be obtained using an infra-red tracked stylus. It is desirable to vie…
Unsupervised Domain Adaptation from Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks
Sven Koehler, Tarique Hussain, Zach Blair +9
Anisotropic multi-slice Cardiac Magnetic Resonance (CMR) Images are conventionally acquired in patient-specific short-axis (SAX) orientation. In specific cardiovascular diseases th…
Heatmap-based 2D Landmark Detection with a Varying Number of Landmarks
Antonia Stern, Lalith Sharan, Gabriele Romano +5
Mitral valve repair is a surgery to restore the function of the mitral valve. To achieve this, a prosthetic ring is sewed onto the mitral annulus. Analyzing the sutures, which are…
How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?
Sven Koehler, Animesh Tandon, Tarique Hussain +7
Planning the optimal time of intervention for pulmonary valve replacement surgery in patients with the congenital heart disease Tetralogy of Fallot (TOF) is mainly based on ventric…
Cross-Domain Conditional Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training
Sandy Engelhardt, Lalith Sharan, Matthias Karck +2
Phantoms for surgical training are able to mimic cutting and suturing properties and patient-individual shape of organs, but lack a realistic visual appearance that captures the he…