[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 …
Synthetic data in health care: A narrative review
A Gonzales, G Guruswamy, SR Smith - PLOS Digital Health, 2023 - journals.plos.org
Data are central to research, public health, and in developing health information technology
(IT) systems. Nevertheless, access to most data in health care is tightly controlled, which …
(IT) systems. Nevertheless, access to most data in health care is tightly controlled, which …
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 …
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 …
Artificial intelligence applications in prostate cancer
Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare
delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology …
delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology …
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
Purpose To perform a systematic review on the research on the application of artificial
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …
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 …
Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy
L Gao, K Xie, X Wu, Z Lu, C Li, J Sun, T Lin, J Sui… - Radiation Oncology, 2021 - Springer
Objective To develop high-quality synthetic CT (sCT) generation method from low-dose
cone-beam CT (CBCT) images by using attention-guided generative adversarial networks …
cone-beam CT (CBCT) images by using attention-guided generative adversarial networks …
A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases
J Lenkowicz, C Votta, M Nardini, F Quaranta… - Radiotherapy and …, 2022 - Elsevier
Introduction This study aims to apply a conditional Generative Adversarial Network (cGAN)
to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance …
to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance …