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Interphase

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Benchmarking human epithelial type 2 interphase cells classification methods on a very large dataset.

Artificial intelligence in medicine
OBJECTIVE: This paper presents benchmarking results of human epithelial type 2 (HEp-2) interphase cell image classification methods on a very large dataset. The indirect immunofluorescence method applied on HEp-2 cells has been the gold standard to i...

An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

Methods (San Diego, Calif.)
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...

Interphase Cell Cycle Staging using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The progression of cells through the cell cycle is a tightly regulated process and is known to be key in maintaining normal tissue architecture and function. Disruption of these orchestrated phases will result in alterations that can lead to many dis...

A machine learning approach for single cell interphase cell cycle staging.

Scientific reports
The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in...

D-MAINS: A Deep-Learning Model for the Label-Free Detection of Mitosis, Apoptosis, Interphase, Necrosis, and Senescence in Cancer Cells.

Cells
BACKGROUND: Identifying cells engaged in fundamental cellular processes, such as proliferation or living/death statuses, is pivotal across numerous research fields. However, prevailing methods relying on molecular biomarkers are constrained by high c...