Comparison Between Feature-Based and Convolutional Neural Network–Based Computer-Aided Diagnosis for Breast Cancer Classification in Digital Breast Tomosynthesis

Siwa Chan* and Jinn-Yi Yeh
Additional contact information
Siwa Chan*: Doctor, Dept. of Medical Imaging, Taichung Tzu Chi Hospital, Taiwan
Jinn-Yi Yeh: Professor, Dept. of Management Information Systems, National Chiayi University, Taiwan

Journal of Biotechnology Research, 2019, vol. 5, issue 1, 1-18

Abstract: Digital breast tomosynthesis (DBT) is a promising new technique for breast cancer diagnosis. DBT has the potential to overcome the tissue superimposition problems that occur on traditional mammograms for tumor detection. However, DBT generates numerous images, thereby creating a heavy workload for radiologists. Therefore, constructing an automatic computer-aided diagnosis (CAD) system for DBT image analysis is necessary. This study compared feature-based CAD and convolutional neural network (CNN)-based CAD for breast cancer classification from DBT images. The research methods included image preprocessing, candidate tumor identification, three-dimensional feature generation, classification, image cropping, augmentation, CNN model design, and deep learning. The precision rates (standard deviation) of the LeNet-based CNN CAD and the feature-based CAD for breast cancer classification were 89.84 (0.013) and 84.46 (0.082), respectively. The T value was -4.091 and the P value was 0.00

Keywords: Breast cancer; Digital breast tomosynthesis; Computer-aided diagnosis; Tumor detection. (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.arpgweb.com/pdf-files/jbr5(1)1-18.pdf (application/pdf)
https://www.arpgweb.com/journal/16/archive/01-2019/1/5 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arp:rjbarp:2019:p:1-18

DOI: 10.32861/jbr.51.1.18

Access Statistics for this article

Journal of Biotechnology Research is currently edited by Dr. Ashraf Abd El-Halim El-Sayed

More articles in Journal of Biotechnology Research from Academic Research Publishing Group Rahim Yar Khan 64200, Punjab, Pakistan.
Bibliographic data for series maintained by Managing Editor ().