73 citations · 195 across the 23 of their papers we have counts for
8 papers · 1 filter
Ensemble Learning and 3D Pix2Pix for Comprehensive Brain Tumor Analysis in Multimodal MRI
Ramy A. Zeineldin, Franziska Mathis-Ullrich
Motivated by the need for advanced solutions in the segmentation and inpainting of glioma-affected brain regions in multi-modal magnetic resonance imaging (MRI), this study present…
Unified HT-CNNs Architecture: Transfer Learning for Segmenting Diverse Brain Tumors in MRI from Gliomas to Pediatric Tumors
Ramy A. Zeineldin, Franziska Mathis-Ullrich
Accurate segmentation of brain tumors from 3D multimodal MRI is vital for diagnosis and treatment planning across diverse brain tumors. This paper addresses the challenges posed by…
Tracking Tumors under Deformation from Partial Point Clouds using Occupancy Networks
Pit Henrich, Jiawei Liu, Jiawei Ge +5
To track tumors during surgery, information from preoperative CT scans is used to determine their position. However, as the surgeon operates, the tumor may be deformed which presen…
LUDO: Low-Latency Understanding of Deformable Objects using Point Cloud Occupancy Functions
Pit Henrich, Franziska Mathis-Ullrich, Paul Maria Scheikl
Accurately determining the shape of deformable objects and the location of their internal structures is crucial for medical tasks that require precise targeting, such as robotic bi…
Learning-Based Autonomous Navigation, Benchmark Environments and Simulation Framework for Endovascular Interventions
Lennart Karstensen, Harry Robertshaw, Johannes Hatzl +8
Endovascular interventions are a life-saving treatment for many diseases, yet suffer from drawbacks such as radiation exposure and potential scarcity of proficient physicians. Robo…
Interactive Surgical Liver Phantom for Cholecystectomy Training
Alexander Schuessler, Rayan Younis, Jamie Paik +3
Training and prototype development in robot-assisted surgery requires appropriate and safe environments for the execution of surgical procedures. Current dry lab laparoscopy phanto…
Sim-To-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery
Paul Maria Scheikl, Eleonora Tagliabue, Balázs Gyenes +4
Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement lea…
LOOC: Localizing Organs using Occupancy Networks and Body Surface Depth Images
Pit Henrich, Franziska Mathis-Ullrich
We introduce a novel approach for the precise localization of 67 anatomical structures from single depth images captured from the exterior of the human body. Our method uses a mult…