Medical image analysis, empowered by artificial intelligence (AI), plays a crucial role in modern healthcare diagnostics. However, the effectiveness of machine learning models hinges on their ability to generalize to diverse patient populations, ...

This paper explores the connections between traditional Large Deformation Diffeomorphic Metric Mapping methods and unsupervised deep-learning approaches for non-rigid registration, particularly emphasizing diffeomorphic registration. The study ...

• Detailed theoretical description of LDDMM and unsupervised deep-learning methods.
• Useful theoretical insights and establish connections between the methods.
• Facilitate a profound understanding of the methodological landscape.
• ...

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 family of PDE-constrained Large Deformation Diffeomorphic Metric Mapping (LDDMM) methods is emerging as a particularly interesting approach for physically meaningful diffeomorphic transformations. The original combination of Gauss–Newton–...

PDE-constrained Stokes Large Deformation Diffeomorphic Metric Mapping (LDDMM) is a particularly interesting framework of physically meaningful diffeomorphic registration methods. PDE-constrained Stokes-LDDMM is formulated as a constrained variational ...

Computational Anatomy aims for the study of variability in anatomical structures from images. Variability is encoded by the spatial transformations existing between anatomical images and a template selected as reference. In the absence of a more ...

This paper focuses on the estimation of statistical atlases of 3D images by means of diffeomorphic transformations. Within a Log-Euclidean framework, the exponential and logarithm maps of diffeomorphisms need to be computed. In this framework, the ...

This paper focuses on the estimation of statistical atlases of 3D images by means of diffeomorphic transformations. Within a Log-Euclidean framework, the exponential and logarithm maps of diffeomorphisms need to be computed. In this framework, the ...

A Java monitor is a Java class that defines one or more synchronized methods. Unlike a regular object, a Java monitor object is intended to be accessed by multiple threads simultaneously. Thus, testing a Java monitor can be significantly different from ...