In the News

Deep Learning-Based Analysis of Macaque Corneal Sub-Basal Nerve Fibers in In Vivo Confocal Microscopy Images This was a presentation given as part of the Blaustein Pain Grand Rounds Conferences held at Johns Hopkins University School of Medicine. It gives an overview of the collaboration between Prof. Mankowski's lab and Voxeleron…

Introduction This post is the third in our series of notes from ARVO.  It follows an initial introductory post about deep learning-based segmentation and a follow-up post that covered prediction models in AI.  This post brings attention back to the more traditional image processing and computer vision methods that underpin…

Introduction This post is the second in our series of notes from ARVO.  It follows an initial introductory post - here - that covered deep learning-based segmentation, with a focus on geographic atrophy.  This dovetails nicely into these notes that cover prediction models in AI. AI in the retina: Prediction…

Introduction ARVO this year was very different to say the least.  And while there was clearly a ton of excellent research presented, which was the one consistent thing about this year’s event, the inability to interact with fellow researchers was the significant down side.  I visited many posters and left…

Voxeleron at ARVO 2021 While disappointed that we cannot meet again this year in person, we at Voxeleron are happy to instead meet virtually. We're available to meet throughout the conference - just use the "Talk Now" button - and would welcomg the opportunity for demos and conversations. In particular,…

Voxeleron has hired Manabu Tokunaga as its Director of Software effective immediately.  Manabu brings decades of experience in radiology, clinical imaging, and EHR interoperability to Voxeleron’s diverse portfolio of AI and digital imaging solutions.  Manabu has both founded and worked at a number of successful medical startups and carries with…

Voxeleron announced today that it has been awarded a Phase II Small Business Innovation Research (SBIR) grant for $1.6M from the National Institutes of Health’s (NIH) National Center for the Advancement of Translational Sciences (NCATS), to develop a true vendor-neutral and cloud-based image analysis and storage solution for eye care…

Included in the current release of Orion is the ability to import arbitrary fundus images, be they color fundus images, auto-fluoroscein or even microperimetry images.  Orion doesn't need to know the field of view and you can either align them manually to the OCT data or automatically when an existing…

We have now submitted our recent work on the deep learning-based segmentation of intra-retinal (IRF), sub-retinal (SRF) and serous pigment epithelial detachments (PEDs) in swept-source optical coherence tomography (SS-OCT) images.  To the best of our knowledge, we are the first to publish such an algorithm using this increasingly important modality. …

Automated Assessment of Corneal Nerves using Deep Learning In vivo corneal microscopy has seen a recent resurgence in interest among both the research and clinical communities.  The cornea is the most densely innervated tissue in the human body so the ability to capture near cellular resolution images of its different…