A Technical Review of Convolutional Neural Network‐Based Mammographic Breast Cancer Diagnosis
This study reviews the technique of convolutional neural network (CNN) applied in a specific
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …
field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on …
Deep learning in medical image super resolution: a review
H Yang, Z Wang, X Liu, C Li, J Xin, Z Wang - Applied Intelligence, 2023 - Springer
Super-resolution (SR) reconstruction is a hot topic in medical image processing. SR implies
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
Convolutional neural networks for no-reference image quality assessment
In this work we describe a Convolutional Neural Network (CNN) to accurately predict image
quality without a reference image. Taking image patches as input, the CNN works in the …
quality without a reference image. Taking image patches as input, the CNN works in the …
Trophectoderm segmentation in human embryo images via inceptioned U-Net
Trophectoderm (TE) is one of the main components of a day-5 human embryo (blastocyst)
that correlates with the embryo's quality. Precise segmentation of TE is an important step …
that correlates with the embryo's quality. Precise segmentation of TE is an important step …
Deep-learning-based image quality enhancement of compressed sensing magnetic resonance imaging of vessel wall: comparison of self-supervised and …
While high-resolution proton density-weighted magnetic resonance imaging (MRI) of
intracranial vessel walls is significant for a precise diagnosis of intracranial artery disease …
intracranial vessel walls is significant for a precise diagnosis of intracranial artery disease …
Transferring deep neural networks for the differentiation of mammographic breast lesions
Abstract Machine learning can help differentiating benign and malignant lesions seen on
mammographic images. Conventional models require handcrafting features for lesion …
mammographic images. Conventional models require handcrafting features for lesion …
[HTML][HTML] Motion artifact correction in fetal MRI based on a Generative Adversarial network method
Fetal MR imaging is subject to artifacts, where the most common type is caused by motion.
These artifacts can appear as blurring and/or ghosting in the affected sequences. Currently if …
These artifacts can appear as blurring and/or ghosting in the affected sequences. Currently if …
A human visual system inspired No-reference image quality assessment method based on local feature descriptors
D Varga - Sensors, 2022 - mdpi.com
Objective quality assessment of natural images plays a key role in many fields related to
imaging and sensor technology. Thus, this paper intends to introduce an innovative quality …
imaging and sensor technology. Thus, this paper intends to introduce an innovative quality …
No‐reference image quality assessment of magnetic resonance images with high‐boost filtering and local features
M Oszust, A Piórkowski… - Magnetic Resonance in …, 2020 - Wiley Online Library
Purpose Subjective quality assessment of displayed magnetic resonance (MR) images
plays a key role in diagnosis and the resultant treatment. Therefore, this study aims to …
plays a key role in diagnosis and the resultant treatment. Therefore, this study aims to …
[HTML][HTML] Generation of synthetic intermediate slices in 3D OCT cubes for improving pathology detection and monitoring
OCT is a non-invasive imaging technique commonly used to obtain 3D volumes of the
ocular structure. These volumes allow the monitoring of ocular and systemic diseases …
ocular structure. These volumes allow the monitoring of ocular and systemic diseases …