Fully automated analysis for bone scintigraphy with artificial neural network: usefulness of bone scan index (BSI) in breast cancer.

Journal: Annals of nuclear medicine

Published Date: Jul 17, 2019

Abstract

OBJECTIVE: Artificial neural network (ANN) technology has been developed for clinical use to analyze bone scintigraphy with metastatic bone tumors. It has been reported to improve diagnostic accuracy and reproducibility especially in cases of prostate cancer. The aim of this study was to evaluate the diagnostic usefulness of quantitative bone scintigraphy with ANN in patients having breast cancer.

Authors

Anri Inaki

Department of Nuclear Medicine, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, 920-8641, Japan. henri@staff.kanazawa-u.ac.jp.
Kenichi Nakajima

Department of Nuclear Medicine, Kanazawa University Hospital.
Hiroshi Wakabayashi
Takafumi Mochizuki

Kanazawa Advanced Medical Center, 13-1 Takara-machi, Kanazawa, 920-8641, Japan.
Seigo Kinuya

Keywords

Automation Bone and Bones Bone Neoplasms Breast Neoplasms Female Fluorodeoxyglucose F18 Humans Image Processing, Computer-Assisted Middle Aged Neural Networks, Computer Positron Emission Tomography Computed Tomography Retrospective Studies Whole Body Imaging

External Resources

View on PubMed Access via DOI PubMed (31317398)

Fully automated analysis for bone scintigraphy with artificial neural network: usefulness of bone scan index (BSI) in breast cancer.

Abstract

Authors

Keywords

External Resources

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