Image segmentation is an important topic in medical image processing. Multicellular tumour spheroids (MTS) are currently one of the most widely employed in vitro model for pre-clinical drug screening in cancer research. Assessing their growing requires the segmentation of images acquired at several time points. This paper presents the preliminary results of an approach for the automatic segmentation of multicellular tumour spheroids. The obtained segmentation accuracy is reasonable demonstrating that the approach proved adequate.

Automatic Segmentation of Multicellular Tumour Spheroids Images During Growing / Introvaia, Alessandra; Muccio, Sara; Bezze, Andrea; Mattu, Clara; Balestra, Gabriella. - ELETTRONICO. - 321:(2024), pp. 230-234. (Intervento presentato al convegno European Federation for Medical Informatics Special Topic Conference (EFMI STC) 2024 - Collaboration across Disciplines for the Health of People, Animals and Ecosystems tenutosi a Timisoara (RO) nel 27 to 29 November 2024) [10.3233/shti241098].

Automatic Segmentation of Multicellular Tumour Spheroids Images During Growing

Introvaia, Alessandra;Muccio, Sara;Bezze, Andrea;Mattu, Clara;Balestra, Gabriella
2024

Abstract

Image segmentation is an important topic in medical image processing. Multicellular tumour spheroids (MTS) are currently one of the most widely employed in vitro model for pre-clinical drug screening in cancer research. Assessing their growing requires the segmentation of images acquired at several time points. This paper presents the preliminary results of an approach for the automatic segmentation of multicellular tumour spheroids. The obtained segmentation accuracy is reasonable demonstrating that the approach proved adequate.
2024
9781643685540
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Descrizione: Automatic Segmentation of Multicellular Tumour Spheroids Images During Growing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2994745