Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma [0.03%]
骨髓瘤患者纵向CT扫描的自动化腰椎识别和分割及结构不确定性分析方法
Djennifer K Madzia-Madzou,Margot Jak,Bart de Keizer et al.
Djennifer K Madzia-Madzou et al.
Objectives: Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis. ...
Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow [0.03%]
基于人工智能辅助配准和体积分割的工作流程对纵向CT扫描中病变评估的改进：一项跨机构阅片研究
Alessa Hering,Max Westphal,Annika Gerken et al.
Alessa Hering et al.
Purpose: AI-assisted techniques for lesion registration and segmentation have the potential to make CT-based tumor follow-up assessment faster and less reader-dependent. However, empirical evidence on the advantages of AI...
Deep learning on longitudinal CT scans: automated prediction of treatment outcomes in hospitalized tuberculosis patients [0.03%]
基于纵向CT图像的深度学习：自动化预测住院结核病患者治疗效果
Mayidili Nijiati,Lin Guo,Abudouresuli Tuersun et al.
Mayidili Nijiati et al.
Three deep learning (DL)-based prediction models (PMs) using longitudinal CT images were developed to predict tuberculosis (TB) treatment outcomes. The internal dataset consists of 493 bacteriologically confirmed TB patients who completed t...
Deep learning and radiomics of longitudinal CT scans for early prediction of tuberculosis treatment outcomes [0.03%]
基于纵向CT影像的深度学习与影像组学预测结核病治疗结局
Mayidili Nijiati,Lin Guo,Abudoukeyoumujiang Abulizi et al.
Mayidili Nijiati et al.
Background: To predict tuberculosis (TB) treatment outcomes at an early stage, prevent poor outcomes ofdrug-resistant tuberculosis(DR-TB) and interrupt transmission. ...
Lung Nodule Malignancy Prediction From Longitudinal CT Scans With Siamese Convolutional Attention Networks [0.03%]
基于双胞胎卷积注意力网络的纵向CT肺癌预测模型
Benjamin P Veasey,Justin Broadhead,Michael Dahle et al.
Benjamin P Veasey et al.
Goal: We propose a convolutional attention-based network that allows for use of pre-trained 2-D convolutional feature extractors and is extendable to multi-time-point classification in a Siamese structure. Methods: Our proposed framework is...
Texture-based Quantification of Centrilobular Emphysema and Centrilobular Nodularity in Longitudinal CT Scans of Current and Former Smokers [0.03%]
基于纹理的量化当前和以前的吸烟者纵向CT扫描中的中央肺小叶性肺气肿和中央肺小叶结节性特征的方法
Shoshana B Ginsburg,Jason Zhao,Stephen Humphries et al.
Shoshana B Ginsburg et al.
Rationale and objectives: The effect of smoking cessation on centrilobular emphysema (CLE) and centrilobular nodularity (CN), two manifestations of smoking-related lung injury on computed tomography (CT) images, has not b...
Multicenter Study
Academic radiology. 2016 Nov;23(11):1349-1358. DOI:10.1016/j.acra.2016.06.002 2016