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A New Automatic Cancer Colony Forming Units Counting Method
Título de la revista
Autores
Roldán N.
Rodriguez L.
Hernandez A.
Cepeda K.
Ondo Méndez, Alejandro Oyono
Cancino Suárez S.L.
Forero M.G.
Lopéz J.M.
Fecha
2019
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Springer
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Abstract
Clonogenic assays are an essential tool to evaluate the survival of cancer cells that have been exposed to a certain dose of radiation. Its result can be used in the generation of strategies for the optimization of radiotherapy treatments. The analysis of this type of data requires that the specialist performs the manual counting of colony forming units (CFU), i.e., find every cell that retains the ability to produce a large progeny. This task is time consuming, prone to errors and the results are not reproducible due to specialist subjective assessment. Digital image processing tools can deal with the flaws described above. This article presents a new technique for automatic CFU counting. The proposed technique extracts the regions of interest (ROIs), where a local segmentation algorithm finds and labels the CFUs in order to quantify them. Results show good sensitivity and specificity performance compared to state-of-the-art software used for CFU detection and counting. © 2019, Springer Nature Switzerland AG.
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Keywords
Cell proliferation , Cells , Cytology , Diseases , Image segmentation , Pattern recognition , Radiotherapy , Cancer , Cell counting , Colony counting , Colony forming units , Radiotherapy treatment , Segmentation algorithms , Sensitivity and specificity , Subjective assessments , Image analysis , Cancer , Cell counting , Cell proliferation , CFU , Colony counting , Image analysis
