IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 15, 2020
We study training deep neural network (DNN) frequency-domain beamformers using simulated and phantom anechoic cysts and compare to training with simulated point target responses. Using simulation, physical phantom, and in vivo scans, we find that tra...
The Plant journal : for cell and molecular biology
Jun 14, 2020
In wheat (Triticum aestivum L) and other cereals, the number of ears per unit area is one of the main yield-determining components. An automatic evaluation of this parameter may contribute to the advance of wheat phenotyping and monitoring. There is ...
In the past decade, a new approach for quantitative analysis of medical images and prognostic modelling has emerged. Defined as the extraction and analysis of a large number of quantitative parameters from medical images, radiomics is an evolving fie...
European journal of nuclear medicine and molecular imaging
Jun 13, 2020
PURPOSE: We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with different scanning hardware and protocols.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jun 12, 2020
Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus cu...
Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmaceutical companies as well as other industries and regulators. The goal of the current study was to develop an in vitro/in silico method for the rapid ...
Biomedical physics & engineering express
Jun 12, 2020
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...
We propose a novel BIRADS-SSDL network that integrates clinically-approved breast lesion characteristics (BIRADS features) into task-oriented semi-supervised deep learning (SSDL) for accurate diagnosis of ultrasound (US) images with a small training ...
Journal of the American Society for Mass Spectrometry
Jun 10, 2020
As the field of mass spectrometry imaging continues to grow, so too do its needs for optimal methods of data analysis. One general need in image analysis is the ability to classify the underlying regions within an image, as healthy or diseased, for e...
Acta radiologica (Stockholm, Sweden : 1987)
Jun 9, 2020
BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.