A review on medical imaging synthesis using deep learning and its clinical applications
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …
clinical application. Specifically, we summarized the recent developments of deep learning …
A review on medical image denoising algorithms
SVM Sagheer, SN George - Biomedical signal processing and control, 2020 - Elsevier
Over the past two decades, medical imaging and diagnostic techniques have gained
immense attraction due to the rapid development in computing, internet, data storage and …
immense attraction due to the rapid development in computing, internet, data storage and …
Domain progressive 3D residual convolution network to improve low-dose CT imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
Structurally-sensitive multi-scale deep neural network for low-dose CT denoising
Computed tomography (CT) is a popular medical imaging modality and enjoys wide clinical
applications. At the same time, the X-ray radiation dose associated with CT scannings raises …
applications. At the same time, the X-ray radiation dose associated with CT scannings raises …
Full-dose PET image estimation from low-dose PET image using deep learning: a pilot study
Positron emission tomography (PET) imaging is an effective tool used in determining
disease stage and lesion malignancy; however, radiation exposure to patients and …
disease stage and lesion malignancy; however, radiation exposure to patients and …
Denoising of 3D magnetic resonance images using a residual encoder–decoder Wasserstein generative adversarial network
Abstract Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is
a critical step in medical image analysis. Over the past few years, many algorithms with …
a critical step in medical image analysis. Over the past few years, many algorithms with …
Radon inversion via deep learning
The Radon transform is widely used in physical and life sciences, and one of its major
applications is in medical X-ray computed tomography (CT), which is significantly important …
applications is in medical X-ray computed tomography (CT), which is significantly important …
TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos
The detection of tiny objects in microscopic videos is a problematic point, especially in large-
scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection …
scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection …
A review on deep learning approaches for low-dose computed tomography restoration
Computed Tomography (CT) is a widely use medical image modality in clinical medicine,
because it produces excellent visualizations of fine structural details of the human body. In …
because it produces excellent visualizations of fine structural details of the human body. In …
Deep learning improves contrast in low-fluence photoacoustic imaging
Low fluence illumination sources can facilitate clinical transition of photoacoustic imaging
because they are rugged, portable, affordable, and safe. However, these sources also …
because they are rugged, portable, affordable, and safe. However, these sources also …