CPA CT肺部三维病理征象的检测与评分

Afonso Nunes, S. Desai, T. Semple, Anand Shah, E. Angelini
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引用次数: 1

摘要

慢性肺曲霉病(CPA)是由曲霉真菌引起的一种复杂类型的真菌感染,主要影响已有肺部病变或免疫系统较弱的人。胸膜增厚,真菌球和空腔在CT扫描上可见,定性地对CPA的程度和严重性进行评分。这项工作的重点是使用深度学习来改进当前的标准,以便在纵向随访中定位和评分CPA标志。我们提出了一个完全在3D中实现的原始框架,结合成像和时间序列编码,提供激活图,CPA严重程度评分和5年死亡率预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3d Pathological Signs Detection And Scoring On CPA CT Lung Scans
Chronic Pulmonary Aspergillosis (CPA) is a complex type of fungal infection caused by the Aspergillus fungus that mostly affects people with pre-existing lung lesions or weakened immune systems. Pleural thicknening, fungal balls and cavities visualized on CT scans are used to score the extent and gravity of CPA, in a qualitative manner. This work focuses on the use of deep-learning to improve current standards in localising and scoring CPA signs for longitudinal follow-up. We propose an original framework fully implemented in 3D, combining imaging and time series encoding, to provide activation maps, CPA severity scores and 5-years mortality prediction.
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