5 citations · 5 across the 6 of their papers we have counts for
6 papers
Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End Registration
Maximilian Tschuchnig, Lukas Lamminger, Philipp Steininger +1
Cone-Beam Computed Tomography (CBCT) is widely used for intraoperative imaging due to its rapid acquisition and low radiation dose. However, CBCT images typically suffer from artif…
Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment
Maximilian Tschuchnig, Lukas Lamminger, Philipp Steininger +1
Cone-Beam Computed Tomography (CBCT) is widely used for real-time intraoperative imaging due to its low radiation dose and high acquisition speed. However, despite its high resolut…
Initial Study On Improving Segmentation By Combining Preoperative CT And Intraoperative CBCT Using Synthetic Data
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Computer-Assisted Interventions enable clinicians to perform precise, minimally invasive procedures, often relying on advanced imaging methods. Cone-beam computed tomography (CBCT)…
CBCTLiTS: A Synthetic, Paired CBCT/CT Dataset For Segmentation And Style Transfer
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Medical imaging is vital in computer assisted intervention. Particularly cone beam computed tomography (CBCT) with defacto real time and mobility capabilities plays an important ro…
Multimodal Learning With Intraoperative CBCT & Variably Aligned Preoperative CT Data To Improve Segmentation
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Cone-beam computed tomography (CBCT) is an important tool facilitating computer aided interventions, despite often suffering from artifacts that pose challenges for accurate interp…
Multi-task Learning To Improve Semantic Segmentation Of CBCT Scans Using Image Reconstruction
Maximilian Ernst Tschuchnig, Julia Coste-Marin, Philipp Steininger +1
Semantic segmentation is a crucial task in medical image processing, essential for segmenting organs or lesions such as tumors. In this study we aim to improve automated segmentati…