[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 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 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 …
A machine learning-based framework for the prediction of cervical cancer risk in women
One of the most common types of cancer in women is cervical cancer, a disease which is the
most prevalent in poor nations, with one woman dying from it every two minutes. It has a …
most prevalent in poor nations, with one woman dying from it every two minutes. It has a …
A review of PET attenuation correction methods for PET-MR
Despite being thirteen years since the installation of the first PET-MR system, the scanners
constitute a very small proportion of the total hybrid PET systems installed. This is in stark …
constitute a very small proportion of the total hybrid PET systems installed. This is in stark …
Synthesis of pseudo-CT images from pelvic MRI images based on an MD-CycleGAN model for radiotherapy
H Sun, Q Xi, R Fan, J Sun, K Xie, X Ni… - Physics in Medicine & …, 2022 - iopscience.iop.org
Objective. A multi-discriminator-based cycle generative adversarial network (MD-CycleGAN)
model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI …
model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI …
Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network
SS Kaushik, M Bylund, C Cozzini… - Physics in Medicine …, 2023 - iopscience.iop.org
Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for
workflow efficiency and reduces radiation to the patient. An important step required to …
workflow efficiency and reduces radiation to the patient. An important step required to …
Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT
This work aims to investigate the clinical feasibility of deep learning-based synthetic CT
images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT) …
images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT) …
Generative adversarial networks in ophthalmology: what are these and how can they be used?
Generative adversarial networks in ophthalmology: what are t... : Current Opinion in
Ophthalmology Generative adversarial networks in ophthalmology: what are these and how can …
Ophthalmology Generative adversarial networks in ophthalmology: what are these and how can …
Synthetic Data Generation via Generative Adversarial Networks in Healthcare: A Systematic Review of Image-and Signal-Based Studies
Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial
intelligence, particularly for unsupervised learning. This systematic review analyzes GAN …
intelligence, particularly for unsupervised learning. This systematic review analyzes GAN …