Diagnostic Performance of the Support Vector Machine Model for Breast Cancer on Ring-Shaped Dedicated Breast Positron Emission Tomography Images.

Journal: Journal of computer assisted tomography

Published Date: Jan 1, 2020

Abstract

OBJECTIVE: The aim of this study was to evaluate the diagnostic ability of support vector machine (SVM) for early breast cancer (BC) using dedicated breast positron emission tomography (dbPET).

Authors

Yoko Satoh
Daiki Tamada

Department of Radiology, University of Yamanashi.
Yoshie Omiya

Department of Radiology, University of Yamanashi, Shimokato, Chuo City, Yamanashi Prefecture, Japan.
Hiroshi Onishi

Department of Radiology, University of Yamanashi, Yamanashi, Japan.
Utaroh Motosugi

Department of Radiology, University of Yamanashi.

Keywords

Adult Aged Aged, 80 and over Breast Breast Neoplasms Female Fluorodeoxyglucose F18 Humans Image Interpretation, Computer-Assisted Middle Aged Positron-Emission Tomography Retrospective Studies Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (32345809)

Diagnostic Performance of the Support Vector Machine Model for Breast Cancer on Ring-Shaped Dedicated Breast Positron Emission Tomography Images.

Abstract

Authors

Keywords

External Resources

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