Hybrid detection of lung nodules on CT scan images

Medical Physics
Lin LuBinsheng Zhao

Abstract

The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithms were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the trai...Continue Reading

References

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Citations

Jan 2, 2016·Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine·Senthilkumar KrishnamurthyUmamaheswari Rengasamy
Nov 29, 2016·IEEE Transactions on Bio-medical Engineering·Yacheng RenJun Zhao
May 12, 2017·Medical Physics·Jingchen MaJun Zhao
Apr 28, 2019·International Journal of Computer Assisted Radiology and Surgery·Li GongLu Wang
Apr 10, 2021·Computers in Biology and Medicine·Lingma SunZhenming Peng
Jun 12, 2021·The British Journal of Radiology·Ayşegül Gürsoy ÇoruhAyten Kayı Cangır
Aug 10, 2021·Journal of Healthcare Engineering·Qing ChaoRong Peng
Feb 12, 2017·Clinical Radiology·B Al MohammadC Mello-Thoms
Aug 28, 2021·International Journal of Computer Assisted Radiology and Surgery·Haiying YuanJunpeng Cheng

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