4 citations · 7 across the 4 of their papers we have counts for
6 papers
Fully Automated Artery-Vein ratio and vascular tortuosity measurement in retinal fundus images
Aashis Khanal, Rolando Estrada
Accurate measurements of abnormalities like Artery-Vein ratio and tortuosity in fundus images is an actively researched task. Most of the research seems to compute such features in…
Fully Automated Tree Topology Estimation and Artery-Vein Classification
Aashis Khanal, Saeid Motevali, Rolando Estrada
We present a fully automatic, graph-based technique for extracting the retinal vascular topology -- that is, how different vessels are connected to each other -- given a single col…
Optic Disc Segmentation using Disk-Centered Patch Augmentation
Saeid Motevali, Aashis Khanal, Rolando Estrada
The optic disc is a crucial diagnostic feature in the eye since changes to its physiognomy is correlated with the severity of various ocular and cardiovascular diseases. While iden…
Peering Beyond the Gradient Veil with Distributed Auto Differentiation
Bradley T. Baker, Aashis Khanal, Vince D. Calhoun +2
Although distributed machine learning has opened up many new and exciting research frontiers, fragmentation of models and data across different machines, nodes, and sites still res…
AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning
Mehdi Mousavi, Aashis Khanal, Rolando Estrada
Machine learning requires data, but acquiring and labeling real-world data is challenging, expensive, and time-consuming. More importantly, it is nearly impossible to alter real da…
Dynamic Deep Networks for Retinal Vessel Segmentation
Aashis Khanal, Rolando Estrada
Segmenting the retinal vasculature entails a trade-off between how much of the overall vascular structure we identify vs. how precisely we segment individual vessels. In particular…