Deformable registration of images obtained from different modalities remains a challenging
task in medical image analysis. This paper addresses this important problem and proposes a …

In this paper, we show how the concept of statistical deformation models (SDMs) can be used
for the construction of average models of the anatomy and their variability. SDMs are built …

This work presents a framework for non-rigid registration which extends and generalizes a
previously developed technique by Rueckert et al. [ 1 ]. We combine multi-resolution …

A novel method is introduced for the generation of landmarks for three-dimensional (3-D)
shapes and the construction of the corresponding 3-D statistical shape models. Automatic …

<?Pub Dtl=""?> EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010)
is a public platform for fair and meaningful comparison of registration algorithms which are …

We propose a method for the reconstruction of volumetric fetal MRI from 2D slices, comprising
super-resolution reconstruction of the volume interleaved with slice-to-volume registration …

Presents a novel method for validation of nonrigid medical image registration. This method
is based on the simulation of physically plausible, biomechanical tissue deformations using …

Deformable image registration is an important tool in medical image analysis. In the case of
lung computed tomography (CT) registration there are three major challenges: large motion …

This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …

The role of breast image analysis in radiologists' interpretation tasks in cancer risk assessment,
detection, diagnosis, and treatment continues to expand. Breast image analysis methods …