Orellana Bernat, Monclús Eva, Navazo Isabel, Bendezú Álvaro, Malagelada Carolina, Azpiroz Fernando
Visualization, Virtual Reality and Graphics Interaction Research Group, UPC-BarcelonaTech, 08034 Barcelona, Spain.
Digestive Department, University Hospital General de Catalunya, 08190 Barcelona, Spain.
Diagnostics (Basel). 2023 Feb 28;13(5):910. doi: 10.3390/diagnostics13050910.
The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension.
结肠内容物分析对胃肠病学家来说是一项有价值的工具，在临床常规中有多种应用。在考虑磁共振成像（MRI）模式时，T2加权图像能够分割结肠腔，而粪便和气体内容物只能在T1加权图像中区分。在本文中，我们提出了一个端到端的准自动框架，该框架包含在T2和T1图像中准确分割结肠以及提取结肠内容物和形态数据所需的所有步骤，以提供结肠内容物和形态数据的量化。因此，医生对饮食的影响和腹胀的机制有了新的认识。
