English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Polymicrogyria (PMG) is a disorder of cortical organization mainly seen inchildren, which can be associated with seizures, developmental delay and motorweakness. PMG is typically diagnosed on magnetic resonance imaging (MRI) butsome cases can be challenging to detect even for experienced radiologists. Inthis study, we create an open pediatric MRI dataset (PPMR) with PMG andcontrols from the Children's Hospital of Eastern Ontario (CHEO), Ottawa,Canada. The differences between PMG MRIs and control MRIs are subtle and thetrue distribution of the features of the disease is unknown. This makesautomatic detection of cases of potential PMG in MRI difficult. We propose ananomaly detection method based on a novel center-based deep contrastive metriclearning loss function (cDCM) which enables the automatic detection of cases ofpotential PMG. Additionally, based on our proposed loss function, we customizea deep learning model structure that integrates dilated convolution,squeeze-and-excitation blocks and feature fusion for our PPMR dataset. Despiteworking with a small and imbalanced dataset our method achieves 92.01% recallat 55.04% precision. This will facilitate a computer aided tool forradiologists to select potential PMG MRIs. To the best of our knowledge, thisresearch is the first to apply machine learning techniques to identify PMG fromMRI only.

A Novel Center-based Deep Contrastive Metric Learning Method for the Detection of Polymicrogyria in Pediatric Brain MRI