Cell Microscopy Imaging: a review on digital image processing applications
Lorenzo Ginori, Juan Valentín
Orozco Morales, Rubén
MetadatosMostrar el registro completo del ítem
The great advances in digital technology as well as in the light microscopy field in recent years, determined that digital cellular imaging had acquired a growing importance in cell biology. New and more sophisticated acquisition methods, like those employed in high content screening, usually produce a huge amount of data which demands the power of computers to analyze them. This approach not only allows increasing speed but also can supersede some limitations inherent to human observers. Computer image analysis in cell microscopy can address diverse tasks like (among others) cell classification and counting, studies on sub-cellular structures and studies on living cells. It also targets fields like pathology, vegetable bio-technology, toxicology, drug development and others. This work reviews a selection of the most updated literature related to digital image processing in cell imaging. Topics covered begin with image restoration with functions like correcting uneven illumination, noise filtering and reduction of blurring. Then image segmentation especially oriented to cell images is addressed, including the separation of cell aggregates and how to evaluate the segmentation effectiveness and compare the algorithms’ performance for specific tasks. Finally, some pattern recognition and classification issues in cell image processing are considered. It is the author’s hope that this review article will help the researchers in this field to have a rapid orientation, which can make easier for them to develop or select an appropriate algorithm, suited to the needs of the cell image processing problem to be solved.
Este documento es reproducido por la biblioteca universitaria de la UCLV bajo el amparo de la legislación cubana vigente sobre derecho de autor. Los usuarios podrán utilizar este material bajo la siguiente licencia: Reconociendo a los autores de la obra mediante las citas y referencias bibliográficas correspondientes, utilizar solo para fines No Comerciales y No realizar reproducciones u obras derivadas.