AIMC Topic: Image Processing, Computer-Assisted

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Semi-supervised GAN-based Radiomics Model for Data Augmentation in Breast Ultrasound Mass Classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The capability of deep learning radiomics (DLR) to extract high-level medical imaging features has promoted the use of computer-aided diagnosis of breast mass detected on ultrasound. Recently, generative adversarial network ...

Automated segmentation of the individual branches of the carotid arteries in contrast-enhanced MR angiography using DeepMedic.

BMC medical imaging
BACKGROUND: Non-invasive imaging is of interest for tracking the progression of atherosclerosis in the carotid bifurcation, and segmenting this region into its constituent branch arteries is necessary for analyses. The purpose of this study was to va...

Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quanti...

Deep learning differentiates between healthy and diabetic mouse ears from optical coherence tomography angiography images.

Annals of the New York Academy of Sciences
We trained a deep learning algorithm to use skin optical coherence tomography (OCT) angiograms to differentiate between healthy and type 2 diabetic mice. OCT angiograms were acquired with a custom-built OCT system based on an akinetic swept laser at ...

Deep Learning Whole-Gland and Zonal Prostate Segmentation on a Public MRI Dataset.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Prostate volume, as determined by magnetic resonance imaging (MRI), is a useful biomarker both for distinguishing between benign and malignant pathology and can be used either alone or combined with other parameters such as prostate-speci...

Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network.

European radiology
OBJECTIVES: To reduce the dose of intravenous iodine-based contrast media (ICM) in CT through virtual contrast-enhanced images using generative adversarial networks.

Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network.

Medical image analysis
Image reconstruction from radio-frequency (RF) data is crucial for ultrafast plane wave ultrasound (PWUS) imaging. Compared with the traditional delay-and-sum (DAS) method based on relatively imprecise assumptions, sparse regularization (SR) method d...

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses.

Ultrasonic imaging
Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis c...

Deep Learning for Automatic Segmentation of Hybrid Optoacoustic Ultrasound (OPUS) Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The highly complementary information provided by multispectral optoacoustics and pulse-echo ultrasound have recently prompted development of hybrid imaging instruments bringing together the unique contrast advantages of both modalities. In the hybrid...

Low-dose PET image noise reduction using deep learning: application to cardiac viability FDG imaging in patients with ischemic heart disease.

Physics in medicine and biology
INTRODUCTION: Cardiac [F]FDG-PET is widely used for viability testing in patients with chronic ischemic heart disease. Guidelines recommend injection of 200-350 MBq [F]FDG, however, a reduction of radiation exposure has become increasingly important,...