Literature DB >> 30239461

The Added Value of Computer-aided Detection of Small Pulmonary Nodules and Missed Lung Cancers.

Jiali Cai1, Dongming Xu2, Shiyuan Liu1, Matthew D Cham2.   

Abstract

Lung cancer at its earliest stage is typically manifested on computed tomography as a pulmonary nodule, which could be detected by low-dose multidetector computed tomography technology and the use of thinner collimation. Within the last 2 decades, computer-aided detection (CAD) of pulmonary nodules has been developed to meet the increasing demand for lung cancer screening computed tomography with a larger set of images per scan. This review introduced the basic techniques and then summarized the up-to-date applications of CAD systems in clinical and research programs and in the low-dose lung cancer screening trials, especially in the detection of small pulmonary nodules and missed lung cancers. Many studies have already shown that the CAD systems could increase the sensitivity and reduce the false-positive rate in the diagnosis of pulmonary nodules, especially for the small and isolated nodules. Further improvements to the current CAD schemes are needed to detect nodules accurately, particularly for subsolid nodules.

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Year:  2018        PMID: 30239461     DOI: 10.1097/RTI.0000000000000362

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  4 in total

1.  Development, Validation, and Comparison of Image-Based, Clinical Feature-Based and Fusion Artificial Intelligence Diagnostic Models in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules.

Authors:  Xiang Wang; Man Gao; Jicai Xie; Yanfang Deng; Wenting Tu; Hua Yang; Shuang Liang; Panlong Xu; Mingzi Zhang; Yang Lu; ChiCheng Fu; Qiong Li; Li Fan; Shiyuan Liu
Journal:  Front Oncol       Date:  2022-06-07       Impact factor: 5.738

2.  Two Novel Nomograms Predicting the Risk and Prognosis of Pancreatic Cancer Patients With Lung Metastases: A Population-Based Study.

Authors:  Wei Zhang; Lichen Ji; Xugang Zhong; Senbo Zhu; Yi Zhang; Meng Ge; Yao Kang; Qing Bi
Journal:  Front Public Health       Date:  2022-05-31

3.  Evaluation of an AI-Powered Lung Nodule Algorithm for Detection and 3D Segmentation of Primary Lung Tumors.

Authors:  Thomas Weikert; Tugba Akinci D'Antonoli; Jens Bremerich; Bram Stieltjes; Gregor Sommer; Alexander W Sauter
Journal:  Contrast Media Mol Imaging       Date:  2019-07-01       Impact factor: 3.161

4.  Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground-glass nodular invasive adenocarcinoma of the lung.

Authors:  Jizheng Tang; Yong Cui; Bowen Li; Xingxing Xue; Feng Tian
Journal:  Thorac Cancer       Date:  2021-07-26       Impact factor: 3.500

  4 in total

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