Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …

The problem of respiratory motion has proved a serious obstacle in developing techniques
to acquire images or guide interventions in abdominal and thoracic organs. Motion models …

Image registration, the process of aligning two or more images, is the core technique of
many (semi-) automatic medical image analysis tasks. Recent studies have shown that deep …

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

Deformable image registration can be time consuming and often needs extensive
parameterization to perform well on a specific application. We present a deformable …

Purpose: The purpose of this work was to describe a versatile algorithm for deformable
image registration with applications in radiotherapy and to validate it on thoracic 4DCT data …

Purpose To develop an accurate and fast deformable image registration (DIR) method for
four‐dimensional computed tomography (4D‐CT) lung images. Deep learning‐based …

Spatial regularization is essential in image registration, which is an ill-posed problem.
Regularization can help to avoid both physically implausible displacement fields and local …

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 …

Deformable image registration is a very important field of research in medical imaging.
Recently multiple deep learning approaches were published in this area showing promising …