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 …

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

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 …

Medical image registration is a vital component of many medical procedures, such as image-
guided radiotherapy (IGRT), as it allows for more accurate dose-delivery and better …

Patient motion impacts single photon emission computed tomography (SPECT), positron
emission tomography (PET) and x-ray computed tomography (CT) by giving rise to …

This paper presents a review of deep learning (DL) in multi-organ segmentation. We
summarized the latest DL-based methods for medical image segmentation and applications …

Registration and fusion of magnetic resonance imaging (MRI) and transrectal ultrasound
(TRUS) of the prostate can provide guidance for prostate brachytherapy. However, accurate …

Artificial intelligence (AI) has great potential to transform the clinical workflow of
radiotherapy. Since the introduction of deep neural networks (DNNs), many AI-based …

Purpose Manual delineation on all breathing phases of lung cancer 4D CT image datasets
can be challenging, exhaustive, and prone to subjective errors because of both the large …