Using the STEGO Neural Network for Scintigraphic Image Analysis-Reference-Cited by-同舟云学术

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Using the STEGO Neural Network for Scintigraphic Image Analysis

Published:2023-05-09 Issue: Volume: Page:
ISSN:
Container-title:INTELS’22
language:
Short-container-title:

Author:

Ulitin Ivan¹²^ORCID,Barulina Marina¹²^ORCID,Velikanova Marina³

Affiliation:

1. Institute of Precision Mechanics and Control, ul Rabochaya, 24, Saratov 410028, Russia

2. Faculty of Computer Science and Information Technology, Saratov National Research State University Named after N.G. Chernyshevsky, St. Astrakhanskaya, 83, Saratov 410012, Russia

3. Laboratory of Radioisotope Diagnostics, Saratov State Medical University Named after V. I. Razumovsky, ul. B. Kazachia, 112, Saratov 410012, Russia

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/33/1/5/pdf

Reference11 articles.

1. West, D.M., and Allen, J.R. (2022, July 14). How Artificial Intelligence Is Transforming the World. Available online: Https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/.

2. Myocardial perfusion scintigraphy: Past, present and future;Notghi;Br. J. Radiol.,2011

3. Deep neural network based artificial intelligence assisted diagnosis of bone scintigraphy for cancer bone metastasis;Zhao;Sci. Rep.,2020

4. The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer;Aoki;Ann. Nucl.,2020

5. Papandrianos, N., Papageorgiou, E., Anagnostis, A., and Feleki, A. (2020). A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans. Appl. Sci., 10.

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