INR-LDDMM: Fluid-based Medical Image Registration Integrating Implicit Neural Representation and Large Deformation Diffeomorphic Metric Mapping

Autor: Zhang, Chulong, Liang, Xiaokun

We propose a flow-based registration framework of medical images based on implicit neural representation. By integrating implicit neural representation and Large Deformable Diffeomorphic Metric Mapping (LDDMM), we employ a Multilayer Perceptron (MLP)

Externí odkaz: http://arxiv.org/abs/2308.09473

LDDMM meets GANs: Generative Adversarial Networks for diffeomorphic registration

Autor: Ramon, Ubaldo, Hernandez, Monica, Mayordomo, Elvira

The purpose of this work is to contribute to the state of the art of deep-learning methods for diffeomorphic registration. We propose an adversarial learning LDDMM method for pairs of 3D mono-modal images based on Generative Adversarial Networks. The

Externí odkaz: http://arxiv.org/abs/2111.12544

LDDMM-Face: Large Deformation Diffeomorphic Metric Learning for Flexible and Consistent Face Alignment

Autor: Yang, Huilin, Lyu, Junyan, Cheng, Pujin, Tang, Xiaoying

We innovatively propose a flexible and consistent face alignment framework, LDDMM-Face, the key contribution of which is a deformation layer that naturally embeds facial geometry in a diffeomorphic way. Instead of predicting facial landmarks via heat

Externí odkaz: http://arxiv.org/abs/2108.00690

xIV-LDDMM Toolkit: A Suite of Image-Varifold Based Technologies for Representing and Mapping 3D Imaging and Spatial-omics Data Simultaneously Across Scales.

Autor: Stouffer KM; Center for Imaging Science, Johns Hopkins University, Baltimore,MD, USA.; Department of Biomedical Engineering, Johns Hopkins University, Baltimore,MD, USA.; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA.; Centre Borelli ENS Paris-Saclay, Gif-Sur-Yvette, France., Chen X; Allen Institute for Brain Science, Seattle,WA, USA., Zeng H; Allen Institute for Brain Science, Seattle,WA, USA., Charlier B; IMAG, Université de Montpellier, CNRS, Montpellier, France., Younes L; Center for Imaging Science, Johns Hopkins University, Baltimore,MD, USA.; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA., Trouvé A; Centre Borelli ENS Paris-Saclay, Gif-Sur-Yvette, France., Miller MI; Center for Imaging Science, Johns Hopkins University, Baltimore,MD, USA.; Department of Biomedical Engineering, Johns Hopkins University, Baltimore,MD, USA.; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA.

Publikováno v: BioRxiv : the preprint server for biology [bioRxiv] 2024 Nov 05. Date of Electronic Publication: 2024 Nov 05.

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