Protozoan parasites are responsible for dramatic, neglected diseases. The automatic determination of intracellular parasite burden from fluorescence microscopy images is a challenging problem. Recent advances in deep learning are transforming this pr...
Grating-based X-ray phase contrast radiography and computed tomography (CT) are promising modalities for future medical applications. However, the ill-posed phase retrieval problem in X-ray phase contrast imaging has hindered its use for quantitative...
Traditional convolutional neural network (CNN) methods rely on dense tensors, which makes them suboptimal for spatially sparse data. In this paper, we propose a CNN model based on sparse tensors for efficient processing of high-resolution shapes repr...
Journal of biomolecular structure & dynamics
Nov 18, 2023
There has been an abrupt increase in brain tumor (BT) related medical cases during the past ten years. The tenth most typical type of tumor affecting millions of people is the BT. The cure rate can, however, rise if it is found early. When evaluating...
INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and ...
Statistical shape modeling (SSM) characterizes anatomical variations in a population of shapes generated from medical images. Statistical analysis of shapes requires consistent shape representation across samples in shape cohort. Establishing this re...
BACKGROUND: Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed tomography (CT) is subject t...
The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (ICU) remains challenging. Computed tomography images are still manually quantified and then underexplo...
Journal of magnetic resonance imaging : JMRI
Nov 16, 2023
BACKGROUND: For time-consuming diffusion-weighted imaging (DWI) of the breast, deep learning-based imaging acceleration appears particularly promising.
BACKGROUND: One of the limitations in leveraging the potential of artificial intelligence in X-ray imaging is the limited availability of annotated training data. As X-ray and CT shares similar imaging physics, one could achieve cross-domain data sha...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.