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Cerebrovascular Disorders

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Topology aware multitask cascaded U-Net for cerebrovascular segmentation.

PloS one
Cerebrovascular segmentation is a crucial preliminary task for many computer-aided diagnosis tools dealing with cerebrovascular pathologies. Over the last years, deep learning based methods have been widely applied to this task. However, classic deep...

Machine Intelligence in Cerebrovascular and Endovascular Neurosurgery.

Advances in experimental medicine and biology
The advent of different realms of computational neurosurgery-including not only machine intelligence but also visualization techniques such as mixed reality and robotic applications-is beginning to impact both open vascular as well as endovascular ne...

A Novel Detection of Cerebrovascular Disease using Multimodal Medical Image Fusion.

Recent advances in inflammation & allergy drug discovery
BACKGROUND: Diseases are medical situations that are allied with specific signs and symptoms. A disease may be instigated by internal dysfunction or external factors like pathogens. Cerebrovascular disease can progress from diverse causes, comprising...

Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.

Scientific reports
Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessitating effective preventative measures, early diagnosis, and treatment to mitigate their impact. A diagnostic model was developed to identify patients ...

Automated Cerebrovascular Segmentation and Visualization of Intracranial Time-of-Flight Magnetic Resonance Angiography Based on Deep Learning.

Journal of imaging informatics in medicine
Time-of-flight magnetic resonance angiography (TOF-MRA) is a non-contrast technique used to visualize neurovascular. However, manual reconstruction of the volume render (VR) by radiologists is time-consuming and labor-intensive. Deep learning-based (...

Toward clearer recognition and easier usefulness: development of a cross-lingual atherosclerotic cerebrovascular disease ontology.

Database : the journal of biological databases and curation
Atherosclerotic cerebrovascular disease could result in a great number of deaths and disabilities. However, it did not acquire enough attention. Less information, statistics, or data on the disease has been revealed. Thus, no systematic concept datas...

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Considering that most patients with low or no significant risk factors can safely undergo noncardiac surgery without additional cardiac evaluation, and given the excessive evaluations often performed in patients undergoing intermediate or...

Detecting cognitive impairment in cerebrovascular disease using gait, dual tasks, and machine learning.

BMC medical informatics and decision making
BACKGROUND: Cognitive impairment is common after a stroke, but it can often go undetected. In this study, we investigated whether using gait and dual tasks could help detect cognitive impairment after stroke.