Tubule Segmentation of Fluorescence Microscopy Images Based on Convolutional Neural Networks With Inhomogeneity Correction.
Soonam LeeChichen FuPaul SalamaKenneth W. DunnEdward J. DelpPublished in: Computational Imaging (2018)
Keyphrases
- fluorescence microscopy images
- convolutional neural networks
- inhomogeneity correction
- visual inspection
- cell nuclei
- mr images
- image segmentation
- segmentation algorithm
- bias field
- image volumes
- magnetic resonance
- intensity inhomogeneity
- image processing
- segmentation method
- fully automatic
- quantitative analysis
- medical images
- multiresolution
- image analysis