BACKGROUND: Intracranial aneurysms (IAs) are a life-threatening disease. Their rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the detection of aneurysms are based on angiographic images. However, critical diagnostic i...
Journal of medical ultrasonics (2001)
Jul 15, 2022
PURPOSE: Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for t...
Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep ...
Sickle cell disease (SCD) is associated with multiple known complications and increased mortality. This study aims to further understand the profile of intensive care unit (ICU) admissions of SCD patients. In this single-center retrospective cohort (...
The organ-on-a-chip (OoC) paves a way for biomedical applications ranging from preclinical to clinical translational precision. The current trends in the in vitro modeling is to reduce the complexity of human organ anatomy to the fundamental cellular...
We analyze an ensemble of organophosphorus compounds to form an unbiased characterization of the information encoded in their X-ray absorption near-edge structure (XANES) and valence-to-core X-ray emission spectra (VtC-XES). Data-driven emergence of ...
The recent pandemic outbreak proved social distancing effective in helping curb the spread of SARS-CoV-2 variants along with the wearing of masks and hand gloves in hospitals and assisted living environments. Health delivery personnel having undergon...
In most deep learning-based brain tumor segmentation methods, training the deep network requires annotated tumor areas. However, accurate tumor annotation puts high demands on medical personnel. The aim of this study is to train a deep network for se...
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