Automated Ovarian Cancer Identification Using End-to-End Deep Learning and Second Harmonic Generation Imaging-Reference-Cited by-同舟云学术

Automated Ovarian Cancer Identification Using End-to-End Deep Learning and Second Harmonic Generation Imaging

Published:2023-07 Issue:4: Biophotonics Volume:29 Page:1-9
ISSN:1077-260X
Container-title:IEEE Journal of Selected Topics in Quantum Electronics
language:
Short-container-title:IEEE J. Select. Topics Quantum Electron.

Author:

Wang Guangxing¹,Zhan Huiling¹,Luo Tianyi¹,Kang Bingzi¹,Li Xiaolu¹,Xi Gangqin¹,Liu Zhiyi²^ORCID,Zhuo Shuangmu¹^ORCID

Affiliation:

1. School of Science, Jimei University, Xiamen, China

2. State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering; International Research Center for Advanced Photonics, Zhejiang University, Hangzhou, Zhejiang, China

Funder

National Key Research and Development Program of China

Natural Science Foundation of Fujian Province

Joint Funds of Fujian Provincial Health and Education Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/2944/9875165/09982414.pdf?arnumber=9982414

Reference43 articles.

1. Intraoperative pathology consultation: error, cause and impact

2. Deep Learning in Medical Imaging

3. Diagnostic Accuracy of Intraoperative Techniques for Margin Assessment in Breast Cancer Surgery

4. Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis

5. Second-harmonic imaging microscopy of living cells

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