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Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning.

Publication ,  Journal Article
Holbrook, MD; Clark, DP; Patel, R; Qi, Y; Bassil, AM; Mowery, YM; Badea, CT
Published in: Tomography
August 7, 2021

We are developing imaging methods for a co-clinical trial investigating synergy between immunotherapy and radiotherapy. We perform longitudinal micro-computed tomography (micro-CT) of mice to detect lung metastasis after treatment. This work explores deep learning (DL) as a fast approach for automated lung nodule detection. We used data from control mice both with and without primary lung tumors. To augment the number of training sets, we have simulated data using real augmented tumors inserted into micro-CT scans. We employed a convolutional neural network (CNN), trained with four competing types of training data: (1) simulated only, (2) real only, (3) simulated and real, and (4) pretraining on simulated followed with real data. We evaluated our model performance using precision and recall curves, as well as receiver operating curves (ROC) and their area under the curve (AUC). The AUC appears to be almost identical (0.76-0.77) for all four cases. However, the combination of real and synthetic data was shown to improve precision by 8%. Smaller tumors have lower rates of detection than larger ones, with networks trained on real data showing better performance. Our work suggests that DL is a promising approach for fast and relatively accurate detection of lung tumors in mice.

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Published In

Tomography

DOI

EISSN

2379-139X

Publication Date

August 7, 2021

Volume

7

Issue

3

Start / End Page

358 / 372

Location

Switzerland

Related Subject Headings

  • X-Ray Microtomography
  • Neural Networks, Computer
  • Mice
  • Lung Neoplasms
  • Lung
  • Deep Learning
  • Animals
 

Citation

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MLA
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Holbrook, M. D., Clark, D. P., Patel, R., Qi, Y., Bassil, A. M., Mowery, Y. M., & Badea, C. T. (2021). Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning. Tomography, 7(3), 358–372. https://doi.org/10.3390/tomography7030032
Holbrook, Matthew D., Darin P. Clark, Rutulkumar Patel, Yi Qi, Alex M. Bassil, Yvonne M. Mowery, and Cristian T. Badea. “Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning.Tomography 7, no. 3 (August 7, 2021): 358–72. https://doi.org/10.3390/tomography7030032.
Holbrook MD, Clark DP, Patel R, Qi Y, Bassil AM, Mowery YM, et al. Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning. Tomography. 2021 Aug 7;7(3):358–72.
Holbrook, Matthew D., et al. “Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning.Tomography, vol. 7, no. 3, Aug. 2021, pp. 358–72. Pubmed, doi:10.3390/tomography7030032.
Holbrook MD, Clark DP, Patel R, Qi Y, Bassil AM, Mowery YM, Badea CT. Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning. Tomography. 2021 Aug 7;7(3):358–372.

Published In

Tomography

DOI

EISSN

2379-139X

Publication Date

August 7, 2021

Volume

7

Issue

3

Start / End Page

358 / 372

Location

Switzerland

Related Subject Headings

  • X-Ray Microtomography
  • Neural Networks, Computer
  • Mice
  • Lung Neoplasms
  • Lung
  • Deep Learning
  • Animals