Felix Ambellan
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View article: Shape-based disease grading via functional maps and graph convolutional networks with application to Alzheimer’s disease
Shape-based disease grading via functional maps and graph convolutional networks with application to Alzheimer’s disease Open
Shape analysis provides methods for understanding anatomical structures extracted from medical images. However, the underlying notions of shape spaces that are frequently employed come with strict assumptions prohibiting the analysis of in…
View article: Joint reconstruction and segmentation in undersampled 3D knee MRI combining shape knowledge and deep learning
Joint reconstruction and segmentation in undersampled 3D knee MRI combining shape knowledge and deep learning Open
Objective. Task-adapted image reconstruction methods using end-to-end trainable neural networks (NNs) have been proposed to optimize reconstruction for subsequent processing tasks, such as segmentation. However, their training typically re…
View article: Sasaki Metric for Spline Models of Manifold-Valued Trajectories
Sasaki Metric for Spline Models of Manifold-Valued Trajectories Open
We propose a generic spatiotemporal framework to analyze manifold-valued measurements, which allows for employing an intrinsic and computationally efficient Riemannian hierarchical model. Particularly, utilizing regression, we represent di…
View article: Author Correction: Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models
Author Correction: Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models Open
View article: Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models
Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models Open
Alternative treatment methods for knee osteoarthritis (OA) are in demand, to delay the young (< 50 Years) patient’s need for osteotomy or knee replacement. Novel interpositional knee spacers shape based on statistical shape model (SSM) app…
View article: Landmark-free Statistical Shape Modeling via Neural Flow Deformations
Landmark-free Statistical Shape Modeling via Neural Flow Deformations Open
Statistical shape modeling aims at capturing shape variations of an anatomical structure that occur within a given population. Shape models are employed in many tasks, such as shape reconstruction and image segmentation, but also shape gen…
View article: SHREC 2022 track on online detection of heterogeneous gestures
SHREC 2022 track on online detection of heterogeneous gestures Open
View article: geomstats/challenge-iclr-2022: Published algorithms (final version)
geomstats/challenge-iclr-2022: Published algorithms (final version) Open
GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
View article: Landmark-Free Statistical Shape Modeling Via Neural Flow Deformations
Landmark-Free Statistical Shape Modeling Via Neural Flow Deformations Open
View article: Rigid Motion Invariant Statistical Shape Modeling based on Discrete Fundamental Forms
Rigid Motion Invariant Statistical Shape Modeling based on Discrete Fundamental Forms Open
We present a novel approach for nonlinear statistical shape modeling that is invariant under Euclidean motion and thus alignment-free. By analyzing metric distortion and curvature of shapes as elements of Lie groups in a consistent Riemann…
View article: Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative
Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative Open
Convolutional neural networks (CNNs) are the state-of-the-art for automated assessment of knee osteoarthritis (KOA) from medical image data. However, these methods lack interpretability, mainly focus on image texture, and cannot completely…
View article: VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images Open
View article: Rigid motion invariant statistical shape modeling based on discrete fundamental forms
Rigid motion invariant statistical shape modeling based on discrete fundamental forms Open
View article: Establishment of a Rolling-Sliding Test Bench to Analyze Abrasive Wear Propagation of Different Bearing Materials for Knee Implants
Establishment of a Rolling-Sliding Test Bench to Analyze Abrasive Wear Propagation of Different Bearing Materials for Knee Implants Open
Currently, new materials for knee implants need to be extensively tested but such tests are expensive in a knee wear simulator in a realized design. However, using a rolling-sliding test bench, these materials can be examined under the sam…
View article: Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative (Supplementary Material)
Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative (Supplementary Material) Open
Convolutional neural networks (CNNs) are the state-of-the-art for automated assessment of knee osteoarthritis (KOA) from medical image data. However, these methods lack interpretability, mainly focus on image texture, and cannot completely…
View article: Geodesic B-score for Improved Assessment of Knee Osteoarthritis
Geodesic B-score for Improved Assessment of Knee Osteoarthritis Open
View article: VerSe: A Vertebrae Labelling and Segmentation Benchmark
VerSe: A Vertebrae Labelling and Segmentation Benchmark Open
This work is a technical report concerning the Large Scale Vertebrae Segmentation Challenge (VerSe) organised in conjunction with the MICCAI 2019. The challenge set-up consisting of two tasks, vertebrae labelling and vertebrae segmentation…
View article: Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative (Supplementary Material)
Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative (Supplementary Material) Open
We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging that combines a priori knowledge of anatomical shape with Convolutional Neural Networks (CNNs). The proposed approach incorporat…