[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …
aiming to overcome the challenges associated with acquiring multiple image modalities for …
Deep learning based synthetic‐CT generation in radiotherapy and PET: a review
Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …
computed tomography (sCT) have received significant research attention as an alternative to …
Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review
Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …
Conversion between CT and MRI images using diffusion and score-matching models
MRI and CT are most widely used medical imaging modalities. It is often necessary to
acquire multi-modality images for diagnosis and treatment such as radiotherapy planning …
acquire multi-modality images for diagnosis and treatment such as radiotherapy planning …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives
Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …
Comparison of different deep learning architectures for synthetic CT generation from MR images
A Bahrami, A Karimian, H Arabi - Physica Medica, 2021 - Elsevier
Purpose Among the different available methods for synthetic CT generation from MR images
for the task of MR-guided radiation planning, the deep learning algorithms have and do …
for the task of MR-guided radiation planning, the deep learning algorithms have and do …
Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer
Background and purpose Delineation of organs at risk (OARs), such as the bladder, rectum
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …
From CNNs to GANs for cross-modality medical image estimation
AS Fard, DC Reutens, V Vegh - Computers in biology and medicine, 2022 - Elsevier
Cross-modality image estimation involves the generation of images of one medical imaging
modality from that of another modality. Convolutional neural networks (CNNs) have been …
modality from that of another modality. Convolutional neural networks (CNNs) have been …
Synthetic CT generation for MRI-guided adaptive radiotherapy in prostate cancer
Current MRI-guided adaptive radiotherapy (MRgART) workflows require fraction-specific
electron and/or mass density maps, which are created by deformable image registration …
electron and/or mass density maps, which are created by deformable image registration …