BACKGROUND: Artificial intelligence (AI)-driven software has been developed and become commercially available within the past few years for the detection of intracranial hemorrhage (ICH) and chronic cerebral microbleeds (CMBs). However, there is curr...
Supervised deep learning needs a large amount of labeled data to achieve high performance. However, in medical imaging analysis, each site may only have a limited amount of data and labels, which makes learning ineffective. Federated learning (FL) ca...
Clinical diagnosis has become very significant in today's health system. The most serious disease and the leading cause of mortality globally is brain cancer which is a key research topic in the field of medical imaging. The examination and prognosi...
Computer methods and programs in biomedicine
Aug 11, 2022
PURPOSE: This paper proposes a CT images and MRI segmentation technology of cardiac aorta based on XR-MSF-U-Net model. The purpose of this method is to better analyze the patient's condition, reduce the misdiagnosis and mortality rate of cardiovascul...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Aug 10, 2022
BACKGROUND AND PURPOSE: Changes of healthy appearing brain tissue after radiotherapy (RT) have been previously observed. Patients undergoing RT may have a higher risk of cognitive decline, leading to a reduced quality of life. The experienced tissue ...
Physical chemistry chemical physics : PCCP
Aug 10, 2022
Water suppression is of paramount importance for many biological and analytical NMR spectroscopy applications. Here, we report the design of a new set of binomial-like radio frequency (RF) pulses that elude water irradiation while exciting or refocus...
Background MRI is frequently used for early diagnosis of axial spondyloarthritis (axSpA). However, evaluation is time-consuming and requires profound expertise because noninflammatory degenerative changes can mimic axSpA, and early signs may therefor...
International journal of neural systems
Aug 9, 2022
Identifying brain abnormalities in autism spectrum disorder (ASD) is critical for early diagnosis and intervention. To explore brain differences in ASD and typical development (TD) individuals by detecting structural features using T1-weighted magnet...
Understanding the brain's functional architecture has been an important topic in the neuroimaging field. A variety of brain network modeling methods have been proposed. Recently, deep neural network-based methods have shown a great advantage in model...
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