The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Transformer, a model comprising attention-based encoder-decoder architecture, have
gained prevalence in the field of natural language processing (NLP) and recently influenced …

Reconstructing 3D MR volumes from multiple motion-corrupted stacks of 2D slices has
shown promise in imaging of moving subjects, eg, fetal MRI. However, existing slice-to …

Magnetic Resonance Imaging (MRI) is a critical imaging technique that provides detailed
visualization of internal structures without harmful radiation. This review focuses on key MRI …

Motivated by the rapid and current progress to develop intelligent image-guided intervention
tools, we aim in this paper to present, a recent review of a specific family of deep learning …

Understanding the relationship between fine-scale spatial organization and biological
function necessitates a tool that effectively combines spatial positions, morphological …

In magnetic resonance imaging (MRI) slice-to-volume reconstruction (SVR) refers to
computational reconstruction of an unknown 3D magnetic resonance volume from stacks of …

Owing to their superior capabilities and advanced achievements, Transformers have
gradually attracted attention with regard to understanding complex brain processing …

Unsupervised deep learning techniques have gained increasing popularity in deformable
medical image registration However, existing methods usually overlook the optimal similarity …

Sonography has been widely used to assess fetal growth and identify fetal anomalies, 1 and
although fetal neurosonography can analyze brain surface anatomy and maturation, 2 it has …