Automatic Segmentation of Multicellular Tumour Spheroids Images During Growing.

Alessandra Introvaia, Sara Muccio, Andrea Bezze, Clara Mattu, Gabriella Balestra
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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.

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在生长过程中自动分割多细胞肿瘤球体图像
图像分割是医学图像处理中的一个重要课题。多细胞肿瘤球(MTS)是目前癌症研究中用于临床前药物筛选最广泛的体外模型之一。评估其生长情况需要对多个时间点获取的图像进行分割。本文介绍了一种自动分割多细胞肿瘤球的方法的初步结果。所获得的分割精度相当高,证明该方法是可行的。
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