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Data from "Deep learning classification of lipid droplets in quantitative phase images"
Dataset   Open access

Data from "Deep learning classification of lipid droplets in quantitative phase images"

Lucas Sheneman
University of Idaho
12/30/2020
DOI: https://doi.org/10.7923/3d0d-yb04
Appears in  Artificial Intelligence and Machine Learning Research

Abstract

deep learning lipid quantitative phase images QPI convolutional neural networks random forest neural network biofuels segmentation semantic segmentation classification gradient boosting linear discriminant analysis support vector machines multilayer perceptron CNN XGBoost SVM LDA ANN Computer Vision Machine Learning Microscopy
Data supporting manuscript from L. Sheneman, G. Stephanopoulos, A.E. Vasdekis titled "Deep learning classification of lipid droplets in quantitative phase images" as currently under review at PLOS ONE. This includes: 1) raw and binary labeled Quantitative Phase Images (QPI) of Y. lipolytica cells used in the analyses described within the manuscript. 2) various derived data including classifier scores, etc.
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Data Access | ZIP compressed directory214.82 MBDownloadView
DataThe complete image library of 7000 Y. lipolytica QPI Images: Library of 7000 8-bit binary masks and corresponding raw 32-bit floating point grayscale tiffs of single Y. lipolytica cells acquired through quantitative phase imagery (QPI)CC BY-NC-SA V4.0,  Open Access

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