activity
20212025
most citedUnderstanding metric-related pitfalls in image analysis validation

204 citations · 381 across the 42 of their papers we have counts for

collaborators
Showing eess.IVShow all

13 papers · 1 filter

eess.IV2025

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…

eess.IV2025

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…

eess.IV2024

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…

eess.IV2024

A Semi-automatic Cranial Implant Design Tool Based on Rigid ICP Template Alignment and Voxel Space Reconstruction

Michael Lackner, Behrus Puladi, Jens Kleesiek +2

In traumatic medical emergencies, the patients heavily depend on cranioplasty - the craft of neurocranial repair using cranial implants. Despite the improvements made in recent yea…

eess.IV2024★ 1 cited

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…

eess.IV2024★ 9 cited

How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation

André Ferreira, Naida Solak, Jianning Li +4

Deep Learning is the state-of-the-art technology for segmenting brain tumours. However, this requires a lot of high-quality data, which is difficult to obtain, especially in the me…

eess.IV2023★ 1 cited

Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy

Zdravko Marinov, Paul F. Jäger, Jan Egger +2

Interactive segmentation is a crucial research area in medical image analysis aiming to boost the efficiency of costly annotations by incorporating human feedback. This feedback ta…

eess.IV2023

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…

eess.IV2023★ 19 cited

CellViT: Vision Transformers for Precise Cell Segmentation and Classification

Fabian Hörst, Moritz Rempe, Lukas Heine +8

Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a c…

eess.IV2022★ 1 cited

Open-Source Skull Reconstruction with MONAI

Jianning Li, André Ferreira, Behrus Puladi +7

We present a deep learning-based approach for skull reconstruction for MONAI, which has been pre-trained on the MUG500+ skull dataset. The implementation follows the MONAI contribu…

eess.IV2022★ 2 cited

Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathology

Oliver Ester, Fabian Hörst, Constantin Seibold +9

The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and gl…

eess.IV2022★ 2 cited

k-strip: A novel segmentation algorithm in k-space for the application of skull stripping

Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala +5

Objectives: Present a novel deep learning-based skull stripping algorithm for magnetic resonance imaging (MRI) that works directly in the information rich k-space. Materials and Me…

eess.IV2021★ 10 cited

AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

Yuan Jin, Antonio Pepe, Jianning Li +6

The aortic vessel tree is composed of the aorta and its branching arteries, and plays a key role in supplying the whole body with blood. Aortic diseases, like aneurysms or dissecti…