Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151400
Title: High-throughput neuron fluorescence imaging through artificial intelligence
Authors: Qiu, Ruidi
Keywords: Engineering::Electrical and electronic engineering::Electronic systems::Biometrics
Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Qiu, R. (2021). High-throughput neuron fluorescence imaging through artificial intelligence. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/151400
Abstract: Fluorescence image analysis is a commonly used method in biological image processing. In practice, different dyes correspond to different staining structures inside the cell. It is difficult for us to manually analyze and correlate images, as it is a tedious process and image interpretation is subjective from person to person. Deep learning has proven to be successful in image classification field. In recent years, it has been widely used in the field of biological image analysis. This project will start from the processing of fluorescence image to tuning parameter of designed convolution neural network. The goal of this project is to build a deep learning model to classify different types of neuron cells for biomedical detection.
URI: https://hdl.handle.net/10356/151400
Fulltext Permission: embargo_restricted_20221231
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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