This paper presents a review of deep learning (DL)-based medical image registration
methods. We summarized the latest developments and applications of DL-based registration …

Deep learning has revolutionized image processing and achieved the-state-of-art performance
in many medical image segmentation tasks. Many deep learning-based methods have …

This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning‐…

Titanium matrix composites (TMCs) reinforced with in situ-formed TiC particles and TiB whiskers
were prepared by reacting titanium and B 4 C via powder metallurgy and hot extrusion. …

Purpose Current clinical application of cone‐beam CT (CBCT) is limited to patient setup.
Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based …

Purpose The purpose of this study was to expedite the contouring process for MRI ‐guided
adaptive radiotherapy ( MR ‐ IGART ), a convolutional neural network ( CNN ) deep‐learning …

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

The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …

The absence of slip systems makes amorphous structure very sensitive to the type of
loading and extremely brittleness in tension. In the present work, The microstructure and …

Deformable image registration (DIR) of 4D-CT images is important in multiple radiation therapy
applications including motion tracking of soft tissue or fiducial markers, target definition, …