35 citations · 37 across the 13 of their papers we have counts for
13 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…
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…
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
Brain Tumour Removing and Missing Modality Generation using 3D WDM
André Ferreira, Gijs Luijten, Behrus Puladi +3
This paper presents the second-placed solution for task 8 and the participation solution for task 7 of BraTS 2024. The adoption of automated brain analysis algorithms to support cl…
Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor Segmentation in MRI-guided Radiotherapy
Nikoo Moradi, André Ferreira, Behrus Puladi +5
Radiation therapy (RT) is essential in treating head and neck cancer (HNC), with magnetic resonance imaging(MRI)-guided RT offering superior soft tissue contrast and functional ima…
Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data
Lukas Heine, Fabian Hörst, Jana Fragemann +6
In industries such as healthcare, finance, and manufacturing, analysis of unstructured textual data presents significant challenges for analysis and decision making. Uncovering pat…
Deep PCCT: Photon Counting Computed Tomography Deep Learning Applications Review
Ana Carolina Alves, André Ferreira, Gijs Luijten +4
Medical imaging faces challenges such as limited spatial resolution, interference from electronic noise and poor contrast-to-noise ratios. Photon Counting Computed Tomography (PCCT…
Multilingual Natural Language Processing Model for Radiology Reports -- The Summary is all you need!
Mariana Lindo, Ana Sofia Santos, André Ferreira +10
The impression section of a radiology report summarizes important radiology findings and plays a critical role in communicating these findings to physicians. However, the preparati…
Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction
Jianning Li, Antonio Pepe, Gijs Luijten +3
In this paper, we introduce a completion framework to reconstruct the geometric shapes of various anatomies, including organs, vessels and muscles. Our work targets a scenario wher…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…