Label-free optical imaging enables automated measurement of human white matter microstructure

White matter pathways allow distant parts of the brain to communicate, supporting memory, emotion, and language. One such ...
EurekAlert!

Mapping long range brain wiring with label free optical imaging

The uncinate fasciculus is a major white matter pathway involved in memory, emotion, and language, but its microscopic ...
EurekAlert!

Non-contact detection of post-regurgitation deep inhalation in calves using infrared thermography and deep learning-based nostril segmentation

An Osaka Metropolitan University research team proposed a non-contact approach for characterizing post-regurgitation deep ...
ascopubs.org

Deep Learning Features Can Improve Radiomics-Based Prostate Cancer Aggressiveness Prediction

Development and Portability of a Text Mining Algorithm for Capturing Disease Progression in Electronic Health Records of Patients With Stage IV Non–Small Cell Lung Cancer Emerging evidence suggests ...
Hosted on MSN

AI is reshaping vessel wall imaging for stroke care

Deep learning is transforming magnetic resonance vessel wall imaging, making it faster, more accurate, and easier to deploy in stroke care. New AI frameworks can automatically segment and reconstruct ...
News Medical

Deep learning method enhances vessel and plaque segmentation in stroke diagnosis

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for ...
Pulmonology Advisor

Enhanced LDCT Lung Cancer Prediction Model Combines Clinical Data, Deep Learning

A model integrating deep learning with clinical and epidemiologic data may significantly improve lung cancer risk prediction based on LDCT screening.
JSTOR Daily

Automated and accurate segmentation of leaf venation networks via deep learning

• Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network ...