Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
Integrated MRI-guided radiotherapy—opportunities and challenges
MRI can help to categorize tissues as malignant or non-malignant both anatomically and
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
Deep learning in medical image registration
Image registration is a fundamental task in multiple medical image analysis applications.
With the advent of deep learning, there have been significant advances in algorithmic …
With the advent of deep learning, there have been significant advances in algorithmic …
[HTML][HTML] A review of deep learning-based three-dimensional medical image registration methods
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 …
guided radiotherapy (IGRT), as it allows for more accurate dose-delivery and better …
Management of motion and anatomical variations in charged particle therapy: past, present, and into the future
The major aim of radiation therapy is to provide curative or palliative treatment to cancerous
malignancies while minimizing damage to healthy tissues. Charged particle radiotherapy …
malignancies while minimizing damage to healthy tissues. Charged particle radiotherapy …
Deep learning–based 4D‐synthetic CTs from sparse‐view CBCTs for dose calculations in adaptive proton therapy
Background Time‐resolved 4D cone beam–computed tomography (4D‐CBCT) allows a
daily assessment of patient anatomy and respiratory motion. However, 4D‐CBCTs suffer …
daily assessment of patient anatomy and respiratory motion. However, 4D‐CBCTs suffer …
ORRN: An ODE-based recursive registration network for deformable respiratory motion estimation with lung 4DCT images
Objective: Deformable Image Registration (DIR) plays a significant role in quantifying
deformation in medical data. Recent Deep Learning methods have shown promising …
deformation in medical data. Recent Deep Learning methods have shown promising …
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning-A Review
M Amirian, D Barco, I Herzig, FP Schilling - Ieee Access, 2024 - ieeexplore.ieee.org
Deep learning based approaches have been used to improve image quality in cone-beam
computed tomography (CBCT), a medical imaging technique often used in applications such …
computed tomography (CBCT), a medical imaging technique often used in applications such …
Deep learning‐based motion compensation for four‐dimensional cone‐beam computed tomography (4D‐CBCT) reconstruction
Abstract Background Motion‐compensated (MoCo) reconstruction shows great promise in
improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality …
improving four‐dimensional cone‐beam computed tomography (4D‐CBCT) image quality …
A modern review of the uncertainties in volumetric imaging of respiratory‐induced target motion in lung radiotherapy
I Vergalasova, J Cai - Medical physics, 2020 - Wiley Online Library
Radiotherapy has become a critical component for the treatment of all stages and types of
lung cancer, often times being the primary gateway to a cure. However, given that radiation …
lung cancer, often times being the primary gateway to a cure. However, given that radiation …