Synthesizing high‐resolution magnetic resonance imaging using parallel cycle‐consistent generative adversarial networks for fast magnetic resonance imaging
Purpose The common practice in acquiring the magnetic resonance (MR) images is to
obtain two‐dimensional (2D) slices at coarse locations while keeping the high in‐plane …
obtain two‐dimensional (2D) slices at coarse locations while keeping the high in‐plane …
Multimodal CT and MR segmentation of head and neck organs-at-risk
Radiotherapy (RT) is a standard treatment modality for head and neck (HaN) cancer that
requires accurate segmentation of target volumes and nearby healthy organs-at-risk (OARs) …
requires accurate segmentation of target volumes and nearby healthy organs-at-risk (OARs) …
Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning
M Douglass, P Gorayski, S Patel, A Santos - Physical and Engineering …, 2023 - Springer
Background Optical scanning technologies are increasingly being utilised to supplement
treatment workflows in radiation oncology, such as surface-guided radiotherapy or 3D …
treatment workflows in radiation oncology, such as surface-guided radiotherapy or 3D …
Attention-guided generative adversarial network to address atypical anatomy in synthetic CT generation
Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown
rapidly in radiation therapy. However, developing class solutions for medical images that …
rapidly in radiation therapy. However, developing class solutions for medical images that …
Unsupervised pseudo CT generation using heterogenous multicentric CT/MR images and CycleGAN: Dosimetric assessment for 3D conformal radiotherapy
Purpose Absorbed dose calculation in magnetic resonance-guided radiation therapy
(MRgRT) is commonly based on pseudo CT (pCT) images. This study investigated the …
(MRgRT) is commonly based on pseudo CT (pCT) images. This study investigated the …
[HTML][HTML] Synthetic computed tomography generation for abdominal adaptive radiotherapy using low-field magnetic resonance imaging
AG Hernandez, P Fau, J Wojak, H Mailleux… - Physics and Imaging in …, 2023 - Elsevier
Abstract Background and Purpose Magnetic Resonance guided Radiotherapy (MRgRT) still
needs the acquisition of Computed Tomography (CT) images and co-registration between …
needs the acquisition of Computed Tomography (CT) images and co-registration between …
Deep learning-based reconstruction can improve the image quality of low radiation dose head CT
Y Nagayama, K Iwashita, N Maruyama, H Uetani… - European …, 2023 - Springer
Objectives To evaluate the image quality of deep learning–based reconstruction (DLR),
model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose …
model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose …
[HTML][HTML] Synthetic CT Generation from 0.35 T MR Images for MR-only Radiation Therapy Planning Using Perceptual Loss Models
X Li, P Yadav, AB McMillan - Practical radiation oncology, 2022 - ncbi.nlm.nih.gov
Aim: Magnetic resonance imaging (MRI) provides excellent soft tissue contrast which makes
it useful for delineating tumor and normal structures in radiotherapy planning, but MRI …
it useful for delineating tumor and normal structures in radiotherapy planning, but MRI …
[PDF][PDF] A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network.
L Deng, H Sun, J Wang, S Huang… - Computers, Materials & …, 2023 - cdn.techscience.cn
In recent years, radiotherapy based only on Magnetic Resonance (MR) images has become
a hot spot for radiotherapy planning research in the current medical field. However …
a hot spot for radiotherapy planning research in the current medical field. However …
Automatic online quality control of synthetic CTs
LD van Harten, JM Wolterink… - … Imaging 2020: Image …, 2020 - spiedigitallibrary.org
Accurate MR-to-CT synthesis is a requirement for MR-only work flows in radiotherapy (RT)
treatment planning. In recent years, deep learning-based approaches have shown …
treatment planning. In recent years, deep learning-based approaches have shown …