most citedImproving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

18 citations · 18 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2019

Fluorescence Image Histology Pattern Transformation using Image Style Transfer

Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Xiaochun Zhao +7

Confocal laser endomicroscopy (CLE) allow on-the-fly in vivo intraoperative imaging in a discreet field of view, especially for brain tumors, rather than extracting tissue for exam…

cs.CV2018

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

Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Michael Mooney +4

Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor…

cs.CV2018

Weakly-Supervised Learning-Based Feature Localization in Confocal Laser Endomicroscopy Glioma Images

Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Claudio Cavallo +7

Confocal Laser Endomicroscope (CLE) is a novel handheld fluorescence imaging device that has shown promise for rapid intraoperative diagnosis of brain tumor tissue. Currently CLE i…

cs.CV201818 cited

Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Nikolay Martirosyan +4

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diag…