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

Confocal laser endomicroscopy (CLE) is an advanced optical fluorescenceimaging technology that has the potential to increase intraoperative precision,extend resection, and tailor surgery for malignant invasive brain tumorsbecause of its subcellular dimension resolution. Despite its promisingdiagnostic potential, interpreting the gray tone fluorescence images can bedifficult for untrained users. In this review, we provide a detaileddescription of bioinformatical analysis methodology of CLE images that beginsto assist the neurosurgeon and pathologist to rapidly connect on-the-flyintraoperative imaging, pathology, and surgical observation into aconclusionary system within the concept of theranostics. We present an overviewand discuss deep learning models for automatic detection of the diagnostic CLEimages and discuss various training regimes and ensemble modeling effect on thepower of deep learning predictive models. Two major approaches reviewed in thispaper include the models that can automatically classify CLE images intodiagnostic/nondiagnostic, glioma/nonglioma, tumor/injury/normal categories andmodels that can localize histological features on the CLE images using weaklysupervised methods. We also briefly review advances in the deep learningapproaches used for CLE image analysis in other organs. Significant advances inspeed and precision of automated diagnostic frame selection would augment thediagnostic potential of CLE, improve operative workflow and integration intobrain tumor surgery. Such technology and bioinformatics analytics lendthemselves to improved precision, personalization, and theranostics in braintumor treatment.

Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning