87 citations · 115 across the 12 of their papers we have counts for
12 papers
Extremely weakly-supervised blood vessel segmentation with physiologically based synthesis and domain adaptation
Peidi Xu, Olga Sosnovtseva, Charlotte Mehlin Sørensen +2
Accurate analysis and modeling of renal functions require a precise segmentation of the renal blood vessels. Micro-CT scans provide image data at higher resolutions, making more sm…
Deep Learning-Assisted Localisation of Nanoparticles in synthetically generated two-photon microscopy images
Rasmus Netterstrøm, Nikolay Kutuzov, Sune Darkner +4
Tracking single molecules is instrumental for quantifying the transport of molecules and nanoparticles in biological samples, e.g., in brain drug delivery studies. Existing intensi…
A Hybrid Approach to Full-Scale Reconstruction of Renal Arterial Network
Peidi Xu, Niels-Henrik Holstein-Rathlou, Stinne Byrholdt Søgaard +5
The renal vasculature, acting as a resource distribution network, plays an important role in both the physiology and pathophysiology of the kidney. However, no imaging techniques a…
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Kenny Erleben +2
Recently, attempts have been made to reduce annotation requirements in feature-based self-explanatory models for lung nodule diagnosis. As a representative, cRedAnno achieves compe…
Open-Full-Jaw: An open-access dataset and pipeline for finite element models of human jaw
Torkan Gholamalizadeh, Faezeh Moshfeghifar, Zachary Ferguson +7
Developing computational models of the human jaw acquired from cone-beam computed tomography (CBCT) scans is time-consuming and labor-intensive. Besides, a quantitative comparison…
Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning
Peidi Xu, Faezeh Moshfeghifar, Torkan Gholamalizadeh +3
Accurate geometry representation is essential in developing finite element models. Although generally good, deep-learning segmentation approaches with only few data have difficulti…
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Oswin Krause +3
Feature-based self-explanatory methods explain their classification in terms of human-understandable features. In the medical imaging community, this semantic matching of clinical…
A multi-patient analysis of the center of rotation trajectories using finite element models of the human mandible
Torkan Gholamalizadeh, Sune Darkner, Peter Lempel Søndergaard +1
Studying different types of tooth movements can help us to better understand the force systems used for tooth position correction in orthodontic treatments. This study considers a…
A direct geometry processing cartilage generation method using segmented bone models from datasets with poor cartilage visibility
Faezeh Moshfeghifar, Max Kragballe Nielsen, José D. Tascón-Vidarte +2
We present a method to generate subject-specific cartilage for the hip joint. Given bone geometry, our approach is agnostic to image modality, creates conforming interfaces, and is…
Mandibular Teeth Movement Variations in Tipping Scenario: A Finite Element Study on Several Patients
Torkan Gholamalizadeh, Sune Darkner, Paolo Maria Cattaneo +2
Previous studies on computational modeling of tooth movement in orthodontic treatments are limited to a single model and fail in generalizing the simulation results to other patien…
Non-Smooth Newton Methods for Deformable Multi-Body Dynamics
Miles Macklin, Kenny Erleben, Matthias Müller +3
We present a framework for the simulation of rigid and deformable bodies in the presence of contact and friction. Our method is based on a non-smooth Newton iteration that solves t…
A Validated Physical Model For Real-Time Simulation of Soft Robotic Snakes
Renato Gasoto, Miles Macklin, Xuan Liu +4
In this work we present a framework that is capable of accurately representing soft robotic actuators in a multiphysics environment in real-time. We propose a constraint-based dyna…