Evaluation of artificial neural networks for the detection of esophagus tumor cells in microscopic hyperspectral images-Reference-Cited by-同舟云学术

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Evaluation of artificial neural networks for the detection of esophagus tumor cells in microscopic hyperspectral images

Published:2022-08 Issue: Volume: Page:
ISSN:
Container-title:2022 25th Euromicro Conference on Digital System Design (DSD)
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Author:

Schroder Anna¹,Maktabi Marianne¹^ORCID,Thieme Rene²^ORCID,Jansen-Winkeln Boris³^ORCID,Gockel Ines³^ORCID,Chalopin Claire¹^ORCID

Affiliation:

1. Innovation Center Computer Assisted Surgery (ICCAS) Leipzig University,Leipzig,Germany

2. University of Leipzig Medical Center,Department of Visceral, Transplantation, Thoracic and Vascular Surgery,Leipzig,Germany

3. Department of General, Visceral, Thoracic and Vasculary Surgery St. Georg hospital of Leipzig,Leipzig,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9996588/9996595/09996959.pdf?arnumber=9996959

Reference17 articles.

1. Quantitative analysis of liver tumors at different stages using microscopic hyperspectral imaging technology

2. Tumor cell identification and classification in esophageal adenocarcinoma specimens by hyperspectral imaging

3. Biopsy Diagnosis of Oral Carcinoma by the Combination of Morphological and Spectral Methods Based on Embedded Relay Lens Microscopic Hyperspectral Imaging System

4. Tumor tissue classification based on micro-hyperspectral technology and deep learning

5. Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

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1. Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery;Journal of Biomedical Optics;2024-05-07

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3. Joint Diagnostic Method of Tumor Tissue Based on Hyperspectral Spectral-Spatial Transfer Features;Diagnostics;2023-06-08

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