[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 …
Artificial general intelligence for radiation oncology
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …
CT synthesis from MRI using multi-cycle GAN for head-and-neck radiation therapy
Y Liu, A Chen, H Shi, S Huang, W Zheng, Z Liu… - … medical imaging and …, 2021 - Elsevier
Abstract Magnetic Resonance Imaging (MRI) guided Radiation Therapy is a hot topic in the
current studies of radiotherapy planning, which requires using MRI to generate synthetic …
current studies of radiotherapy planning, which requires using MRI to generate synthetic …
Conditional GAN with 3D discriminator for MRI generation of Alzheimer's disease progression
Many studies aim to predict the degree of deformation on affected brain regions as
Alzheimer's disease (AD) progresses. However, those studies have been often limited since …
Alzheimer's disease (AD) progresses. However, those studies have been often limited since …
GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy
With the massive proliferation of data-driven algorithms, such as deep learning-based
approaches, the availability of high-quality data is of great interest. Volumetric data is very …
approaches, the availability of high-quality data is of great interest. Volumetric data is very …
Dc-cyclegan: bidirectional ct-to-mr synthesis from unpaired data
Magnetic resonance (MR) and computer tomography (CT) images are two typical types of
medical images that provide mutually-complementary information for accurate clinical …
medical images that provide mutually-complementary information for accurate clinical …
Conditional GAN with an attention-based generator and a 3D discriminator for 3D medical image generation
Abstract Conditional Generative Adversarial Networks (cGANs) are a set of methods able to
synthesize images that match a given condition. However, existing models designed for …
synthesize images that match a given condition. However, existing models designed for …
[PDF][PDF] GAN-based generation of realistic 3D data: A systematic review and taxonomy
Data has become the most valuable resource in today's world. With the massive proliferation
of data-driven algorithms, such as deep learning-based approaches, the availability of data …
of data-driven algorithms, such as deep learning-based approaches, the availability of data …
Self-supervised ultrasound to MRI fetal brain image synthesis
J Jiao, AIL Namburete… - … on Medical Imaging, 2020 - ieeexplore.ieee.org
Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing
brain but is not suitable for second-trimester anomaly screening, for which ultrasound (US) is …
brain but is not suitable for second-trimester anomaly screening, for which ultrasound (US) is …
Deep learning for brain disorders: from data processing to disease treatment
In order to reach precision medicine and improve patients' quality of life, machine learning is
increasingly used in medicine. Brain disorders are often complex and heterogeneous, and …
increasingly used in medicine. Brain disorders are often complex and heterogeneous, and …