48 citations · 59 across the 30 of their papers we have counts for
32 papers
Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement
Susanne Schaub, Florentin Bieder, Matheus L. Oliveira +5
Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captures a small part of the patient…
4D Pencil Beam Treatment Plan with Conditional Weight Predictions
Nair N von Muehlenen, Florentin Bieder, Philippe C Cattin
Objective. This work aims to accelerate our four-dimensional (4D) proton pencil beam delivery strategy, which incorporates respiratory motion into a dynamic treatment plan, to impr…
SA-Profile: Automated Sulcus Angle Profiling from Super-Resolution MRI
Michael Wehrli, Leo Widmer, Edwin Li +5
Trochlear dysplasia (TD) is an abnormality of the femoral trochlea associated with anterior knee pain and patellar instability. The sulcus angle (SA) is used to assess trochlear mo…
Generalizing Soft Tissue Deformation and Force Prediction Across Material Stiffness and Geometry
Madina Kojanazarova, Sidaty El Hadramy, Philippe C. Cattin
Accurate soft tissue simulation is essential for surgical training, pre-operative planning, and haptic feedback systems. While learning-based surrogate models trained on data using…
Modelling Geographic Atrophy Progression using Implicit Neural Representations
Simone Sarrocco, Paul Friedrich, Florentin Bieder +4
Age-related Macular Degeneration (AMD) is the major cause of blindness in the Western world. Its late dry phase is characterised by irreversible atrophic areas, namely Geographic A…
HyperShape: Hyperelasticity Across Diverse Shapes
Leo Widmer, Sidaty El Hadramy, Stéphane Cotin +1
Hyperelastic deformations are highly sensitive to domain geometry and boundary conditions, making generalization across both a critical capability for neural operators applied to t…
Portable surrogate-free 4D MRI from standard fast multi-slice 2D MRI via implicit neural representations
Muheng Li, Xinyang Wu, Xia Li +5
Four-dimensional MRI (4D MRI) characterizes respiratory organ motion, yet existing reconstruction pipelines are tightly coupled to specific acquisition platforms (e.g., non-Cartesi…
DefSynUS: Real-time Patient-specific Intrahepatic Vessel Identification via Deformation-Aware CT-US Domain Adaptation
Karl-Philippe Beaudet, Yordanka Velikova, Sidaty El Hadramy +4
Purpose: Laparoscopic ultrasound (LUS) enhances the safety of liver surgery by visualizing intrahepatic vessels in real-time. Still, vessel identification remains difficult due to…
NOIR: Neural Operator mapping for Implicit Representations
Sidaty El Hadramy, Nazim Haouchine, Michael Wehrli +1
This paper presents NOIR, a framework that reframes core medical imaging tasks as operator learning between continuous function spaces, challenging the prevailing paradigm of discr…
3D CBCT Artefact Removal Using Perpendicular Score-Based Diffusion Models
Susanne Schaub, Florentin Bieder, Matheus L. Oliveira +4
Cone-beam computed tomography (CBCT) is a widely used 3D imaging technique in dentistry, offering high-resolution images while minimising radiation exposure for patients. However,…
Longitudinal NSCLC Treatment Progression via Multimodal Generative Models
Massimiliano Mantegna, Elena Mulero Ayllón, Alice Natalina Caragliano +10
Predicting tumor evolution during radiotherapy is a clinically critical challenge, particularly when longitudinal changes are driven by both anatomy and treatment. In this work, we…
AutoFFS: Adversarial Deformations for Facial Feminization Surgery Planning
Paul Friedrich, Florentin Bieder, Florian M. Thieringer +1
Facial feminization surgery (FFS) is a key component of gender affirmation for transgender and gender diverse patients, aiming to reshape craniofacial structures toward a female mo…
End2Reg: Learning Task-Specific Segmentation for Markerless Registration in Spine Surgery
Lorenzo Pettinari, Sidaty El Hadramy, Michael Wehrli +4
Intraoperative navigation in spine surgery demands millimeter-level accuracy. Currently, this is achieved through radiation-intensive intraoperative imaging and bone-anchored marke…
Deep Generative Models for Enhanced Vitreous OCT Imaging
Simone Sarrocco, Philippe C. Cattin, Peter M. Maloca +2
Purpose: To evaluate deep learning (DL) models for enhancing vitreous optical coherence tomography (OCT) image quality and reducing acquisition time. Methods: Conditional Denoising…
CPT-4DMR: Continuous sPatial-Temporal Representation for 4D-MRI Reconstruction
Xinyang Wu, Muheng Li, Xia Li +5
Four-dimensional MRI (4D-MRI) is an promising technique for capturing respiratory-induced motion in radiation therapy planning and delivery. Conventional 4D reconstruction methods,…
Optimization-Based Calibration for Intravascular Ultrasound Volume Reconstruction
Karl-Philippe Beaudet, Sidaty El Hadramy, Philippe C Cattin +2
Intraoperative ultrasound images are inherently challenging to interpret in liver surgery due to the limited field of view and complex anatomical structures. Bridging the gap betwe…
Towards Diagnostic Quality Flat-Panel Detector CT Imaging Using Diffusion Models
Hélène Corbaz, Anh Nguyen, Victor Schulze-Zachau +5
Patients undergoing a mechanical thrombectomy procedure usually have a multi-detector CT (MDCT) scan before and after the intervention. The image quality of the flat panel detector…
Edge2Prompt: Modality-Agnostic Model for Out-of-Distribution Liver Segmentation
Nathan Hollet, Oumeymah Cherkaoui, Philippe C. Cattin +1
Liver segmentation is essential for preoperative planning in interventions like tumor resection or transplantation, but implementation in clinical workflows faces challenges due to…
Towards MR-Based Trochleoplasty Planning
Michael Wehrli, Alicia Durrer, Paul Friedrich +5
To treat Trochlear Dysplasia (TD), current approaches rely mainly on low-resolution clinical Magnetic Resonance (MR) scans and surgical intuition. The surgeries are planned based o…
fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
Alicia Durrer, Florentin Bieder, Paul Friedrich +3
Healthy tissue inpainting has significant applications, including the generation of pseudo-healthy baselines for tumor growth models and the facilitation of image registration. In…
cIDIR: Conditioned Implicit Neural Representation for Regularized Deformable Image Registration
Sidaty El Hadramy, Oumeymah Cherkaoui, Philippe C. Cattin
Regularization is essential in deformable image registration (DIR) to ensure that the estimated Deformation Vector Field (DVF) remains smooth, physically plausible, and anatomicall…
Conditional Graph Neural Network for Predicting Soft Tissue Deformation and Forces
Madina Kojanazarova, Florentin Bieder, Robin Sandkühler +1
Soft tissue simulation in virtual environments is becoming increasingly important for medical applications. However, the high deformability of soft tissue poses significant challen…
MedFuncta: A Unified Framework for Learning Efficient Medical Neural Fields
Paul Friedrich, Florentin Bieder, Julian McGinnis +3
Research in medical imaging primarily focuses on discrete data representations that poorly scale with grid resolution and fail to capture the often continuous nature of the underly…
Generating 3D Pseudo-Healthy Knee MR Images to Support Trochleoplasty Planning
Michael Wehrli, Alicia Durrer, Paul Friedrich +6
Purpose: Trochlear Dysplasia (TD) is a common malformation in adolescents, leading to anterior knee pain and instability. Surgical interventions such as trochleoplasty require prec…