AIMC Topic: Image Cytometry

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Deep Learning in Image Cytometry: A Review.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Dec 19, 2018
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and how it is ap...
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Animals Deep Learning Image Processing, Computer-Assisted Microscopy Image Cytometry
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Automated detection of cancer cells in effusion specimens by DNA karyometry.

Cancer cytopathology Oct 19, 2018
BACKGROUND: The average sensitivity of conventional cytology for the identification of cancer cells in effusion specimens is only approximately 58%. DNA image cytometry (DNA-ICM), which exploits the DNA content of morphologically suspicious nuclei me...
Humans Machine Learning Sensitivity and Specificity Neoplasms Diagnosis, Computer-Assisted Epithelium Aneuploidy Cell Nucleus DNA, Neoplasm Image Cytometry Karyometry
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An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

Methods (San Diego, Calif.) Sep 2, 2016
Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differe...
Humans Machine Learning Software Reproducibility of Results Image Processing, Computer-Assisted Flow Cytometry Cell Count Workflow Jurkat Cells Mitosis Interphase Image Cytometry
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