Deep iterative vessel segmentation in OCT angiography

Eigensnakes for Vessel Segmentation in Angiography

In this paper we introduce a new deformable model, called eigensnake, for segmentation of elongated structures in a probabilistic framework. Instead of snake attraction by specific image features extracted independently of the snake, our eigensnake learns an optimal object description and searches for such image feature in the target image. This is achieved applying principal component analysis...

Deep Learning based Retinal OCT Segmentation

Objective To evaluate the efficacy of methods that use deep learning (DL) for the automatic fine-grained segmentation of optical coherence tomography (OCT) images of the retina.

Retinal Vessel Segmentation using Deep Neural Networks

Automatic segmentation of blood vessels in fundus images is of great importance as eye diseases as well as some systemic diseases cause observable pathologic modifications. It is a binary classification problem: for each pixel we consider two possible classes (vessel or non-vessel). We use a GPU implementation of deep max-pooling convolutional neural networks to segment blood vessels. We test o...

Swept-Source OCT Angiography: SS OCT AngioTM

Advancing OCT Angiography

(FA) or indocyanine green (ICG) as the fluorescent contrast agent – has been the standard method of its assessment, but both have a number of problems associated with their use. The systemic intravenous injection of fluorescein or ICG can result in systemic adverse events like nausea and allergic reactions (occasionally anaphylaxis), and it consumes both time and resources: patients have to be ...