Search Results for author: Jan-Jakob Sonke

Found 22 papers, 9 papers with code

Space-Time Continuous PDE Forecasting using Equivariant Neural Fields

no code implementations10 Jun 2024 David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Efstratios Gavves, Erik J. Bekkers

Recently, Conditional Neural Fields (NeFs) have emerged as a powerful modelling paradigm for PDEs, by learning solutions as flows in the latent space of the Conditional NeF.

Domain Adaptation with Cauchy-Schwarz Divergence

1 code implementation30 May 2024 Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, Efstratios Gavves

Furthermore, we illustrate that the CS divergence enables a simple estimator on the discrepancy of both marginal and conditional distributions between source and target domains in the representation space, without requiring any distributional assumptions.

Multi-class Classification Unsupervised Domain Adaptation

End-to-end Adaptive Dynamic Subsampling and Reconstruction for Cardiac MRI

no code implementations15 Mar 2024 George Yiasemis, Jan-Jakob Sonke, Jonas Teuwen

Accelerating dynamic MRI is essential for enhancing clinical applications, such as adaptive radiotherapy, and improving patient comfort.

Dynamic Reconstruction MRI Reconstruction

Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation

1 code implementation29 Jan 2024 Jie Liu, Wenzhe Yin, Haochen Wang, Yunlu Chen, Jan-Jakob Sonke, Efstratios Gavves

Existing prototype-based methods rely on support prototypes to guide the segmentation of query point clouds, but they encounter challenges when significant object variations exist between the support prototypes and query features.

Point Cloud Segmentation Transfer Learning

Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT

no code implementations20 Jan 2024 Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

Our method surpasses classical and deep learning baselines, including LIRE, on the thorax test set.

Task-Driven Wavelets using Constrained Empirical Risk Minimization

no code implementations CVPR 2024 Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke, Jonas Teuwen

Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions.

How to Train Neural Field Representations: A Comprehensive Study and Benchmark

1 code implementation CVPR 2024 Samuele Papa, Riccardo Valperga, David Knigge, Miltiadis Kofinas, Phillip Lippe, Jan-Jakob Sonke, Efstratios Gavves

With this library, we perform a comprehensive study that investigates the effects of different hyperparameters on fitting NeFs for downstream tasks.

Benchmarking

JSSL: Joint Supervised and Self-supervised Learning for MRI Reconstruction

no code implementations27 Nov 2023 George Yiasemis, Nikita Moriakov, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen

In this paper, we introduce JSSL (Joint Supervised and Self-supervised Learning), a novel training approach for deep learning-based MRI reconstruction algorithms aimed at enhancing reconstruction quality in scenarios where target dataset(s) containing fully sampled k-space measurements are unavailable.

MRI Reconstruction Self-Supervised Learning

Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms

1 code implementation CVPR 2024 Joren Brunekreef, Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke, Jonas Teuwen

If one only requires only marginal calibration on the image level, this calibration set consists of all individual pixels in the images available for calibration.

Conformal Prediction Image Segmentation +1

Deep Cardiac MRI Reconstruction with ADMM

no code implementations10 Oct 2023 George Yiasemis, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

In this work, inspired by related work in accelerated MRI reconstruction, we present a deep learning (DL)-based method for accelerated cine and multi-contrast reconstruction in the context of dynamic cardiac imaging.

Anatomy Dynamic Reconstruction +1

vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems

no code implementations18 Sep 2023 George Yiasemis, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

In this study, we propose vSHARP (variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse Problems), a novel DL-based method for solving ill-posed inverse problems arising in MI.

MRI Reconstruction

Neural Modulation Fields for Conditional Cone Beam Neural Tomography

no code implementations17 Jul 2023 Samuele Papa, David M. Knigge, Riccardo Valperga, Nikita Moriakov, Miltos Kofinas, Jan-Jakob Sonke, Efstratios Gavves

Conventional Computed Tomography (CT) methods require large numbers of noise-free projections for accurate density reconstructions, limiting their applicability to the more complex class of Cone Beam Geometry CT (CBCT) reconstruction.

Computed Tomography (CT)

Constrained Empirical Risk Minimization: Theory and Practice

2 code implementations9 Feb 2023 Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke, Jonas Teuwen

Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions.

Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN

1 code implementation25 Jan 2023 David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke

Performant Convolutional Neural Network (CNN) architectures must be tailored to specific tasks in order to consider the length, resolution, and dimensionality of the input data.

On Retrospective k-space Subsampling schemes For Deep MRI Reconstruction

no code implementations20 Jan 2023 George Yiasemis, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen

This work investigates the impact of the $k$-space subsampling scheme on the quality of reconstructed accelerated MRI measurements produced by trained DL models.

MRI Reconstruction

Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network

no code implementations9 Jan 2023 Jie Liu, Yanqi Bao, Wenzhe Yin, Haochen Wang, Yang Gao, Jan-Jakob Sonke, Efstratios Gavves

However, the appearance variations between objects from the same category could be extremely large, leading to unreliable feature matching and query mask prediction.

Few-Shot Semantic Segmentation

Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation

no code implementations CVPR 2022 Jie Liu, Yanqi Bao, Guo-Sen Xie, Huan Xiong, Jan-Jakob Sonke, Efstratios Gavves

Specifically, in DPCN, a dynamic convolution module (DCM) is firstly proposed to generate dynamic kernels from support foreground, then information interaction is achieved by convolution operations over query features using these kernels.

Few-Shot Semantic Segmentation Semantic Segmentation

Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction

3 code implementations CVPR 2022 George Yiasemis, Jan-Jakob Sonke, Clarisa Sánchez, Jonas Teuwen

Magnetic Resonance Imaging can produce detailed images of the anatomy and physiology of the human body that can assist doctors in diagnosing and treating pathologies such as tumours.

Anatomy MRI Reconstruction

Subpixel object segmentation using wavelets and multi resolution analysis

no code implementations28 Oct 2021 Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.

Decoder Object +1

Subpixel object segmentation using wavelets and multiresolution analysis

no code implementations29 Sep 2021 Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.

Decoder Object +1

Deep MRI Reconstruction with Radial Subsampling

1 code implementation17 Aug 2021 George Yiasemis, Chaoping Zhang, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen

In spite of its extensive adaptation in almost every medical diagnostic and examinatorial application, Magnetic Resonance Imaging (MRI) is still a slow imaging modality which limits its use for dynamic imaging.

MRI Reconstruction

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