Volume Visualization for Improving CT Lung Nodule Detection

Adam Huang, Chung Wei Lee, Chung Yi Yang, Hon Man Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Inspired by the outstanding performance of deep convolutional neural networks (CNNs), nowadays modern computer-aided detection (CAD) systems for CT lung nodules generally delve into 2D or 3D CNNs directly without considering traditional image preprocessing techniques. However, detection of large pulmonary nodules and masses are computationally challenging, especially for 3D CNNs. In this paper, we examine the possibility of using volume visualized CT thin-slab images with 2D CNNs to reduce computation complexity and improve CAD performance. We tested 4 types of images: original 2D CT, 2D projection of thin slabs, mixture by arranging original and projection in different color channels, and mixture by the pixelwise maximum intensity of original CT and projection. We evaluated these images on a dataset of 30 CT scans with 30 different-sized nodules and masses on GoogLeNet via a transfer learning and cross validation paradigm. We found that projection visualization alone had a better or equal area-under curve score for all the different-sized nodules and masses. However, mixture by the maximum of CT and projection demonstrated a preferred performance with a true positive rate of 0.8 and a false positive rate of 0.046 in detecting large nodules and masses.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1035-1038
Number of pages4
ISBN (Electronic)9781538613115
DOIs
StatePublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country/TerritoryGermany
CityBerlin
Period23/07/1927/07/19

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