Samuel Fulton

Abstract The complex and highly intertwined morphology of activated platelets within thrombi poses significant challenges for segmentation. In this work, we present a robust dual-network pipeline cell and organelle segmentation.

Abstract Nitrogen-vacancy centers in nanodiamonds exhibit photo-stability and biocompatibility that make them promising candidates for versatile biological sensors. In the present work, we study the dependence of NV-nanodiamond fluorescence on the pH of the surrounding ionic aqueous solution. Band-bending effects and modified ion migration rates may be the potential mechanisms underlying the observed pH sensitivity.

Abstract Here we develop a robust machine vision pipeline for cell and organelle segmentation within vEM datasets. We collect neural network predictions along multiple planes, capturing 3D correlations using only 2D neural networks. We segment and analyze hundreds of platelets and report quantitative morphological measurements. We apply our segmentation pipeline to the CREMI neuron segmentation challenge data and provide state-of-the-art results.