论文标题
基于纹理的形态操作的预后能力在肺癌的放射线学研究中
Prognostic Power of Texture Based Morphological Operations in a Radiomics Study for Lung Cancer
论文作者
论文摘要
现在已经确立了放射线学特征对预测患者预后的重要性。对预后特征的早期研究可以导致更有效的治疗个性化。因此，提出了通过基于数学形态的操作获得的新的放射组学特征。他们的研究是在患有非小细胞肺癌（NSCLC）患者的开放数据库上进行的。肿瘤特征是从CT图像中提取的，并通过PCA和Kaplan-Meier生存分析进行分析，以选择最相关的生存分析。在研究的1,589个特征中，发现32个与预测患者生存有关：27个经典放射线特征和5个MM特征（包括粒度和形态协方差特征）。这些特征将有助于预后模型，并最终有助于临床决策和患者的治疗过程。
The importance of radiomics features for predicting patient outcome is now well-established. Early study of prognostic features can lead to a more efficient treatment personalisation. For this reason new radiomics features obtained through mathematical morphology-based operations are proposed. Their study is conducted on an open database of patients suffering from Nonsmall Cells Lung Carcinoma (NSCLC). The tumor features are extracted from the CT images and analyzed via PCA and a Kaplan-Meier survival analysis in order to select the most relevant ones. Among the 1,589 studied features, 32 are found relevant to predict patient survival: 27 classical radiomics features and five MM features (including both granularity and morphological covariance features). These features will contribute towards the prognostic models, and eventually to clinical decision making and the course of treatment for patients.
