8 papers
++nnU-Net: Scaling nnU-Net with Prefix-Based Data Augmentation
Ana Sofia Santos, André Ferreira, Gijs Luijten +6
The nnU-Net has demonstrated continuous success in medical segmentation tasks, which heavily rely on the availability and diversity of annotated biomedical data. However, assemblin…
VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation
Nikoo Moradi, Gijs Luijten, Behrus Hinrichs-Puladi +4
Diffusion models produce high-quality synthetic data but suffer from slow inference. We propose 3D Variable-Step Denoising Diffusion Probabilistic Model (VS-DDPM) a framework engin…
Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound
Gijs Luijten, Roberto Maria Scardigno, Lisle Faray de Paiva +5
Ultrasound (US) is widely accessible and radiation-free but has a steep learning curve due to its dynamic nature and non-standard imaging planes. Additionally, the constant need to…
Enhancing Privacy: The Utility of Stand-Alone Synthetic CT and MRI for Tumor and Bone Segmentation
André Ferreira, Kunpeng Xie, Caroline Wilpert +12
AI requires extensive datasets, while medical data is subject to high data protection. Anonymization is essential, but poses a challenge for some regions, such as the head, as iden…
From Screen to Space: Evaluating Siemens' Cinematic Reality
Gijs Luijten, Lisle Faray de Paiva, Sebastian Krueger +8
As one of the first research teams with full access to Siemens' Cinematic Reality, we evaluate its usability and clinical potential for cinematic volume rendering on the Apple Visi…
Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink
Lisle Faray de Paiva, Gijs Luijten, Ana Sofia Ferreira Santos +4
Medical imaging segmentation is essential in clinical settings for diagnosing diseases, planning surgeries, and other procedures. However, manual annotation is a cumbersome and eff…