Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks-Reference-Cited by-同舟云学术

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Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks

Published:2019 Issue:5 Volume:144 Page:1642-1653
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Berisha Sebastian¹²³⁴^ORCID,Lotfollahi Mahsa¹²³⁴^ORCID,Jahanipour Jahandar¹²³⁴^ORCID,Gurcan Ilker¹²³⁴^ORCID,Walsh Michael⁵⁶⁷⁴^ORCID,Bhargava Rohit⁸⁹¹⁰¹¹¹²^ORCID,Van Nguyen Hien¹²³⁴^ORCID,Mayerich David¹²³⁴^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering

2. University of Houston

3. Houston

4. USA

5. Department of Pathology

6. University of Illinois at Chicago

7. Chicago

8. Departments of Bioengineering

9. Electrical & Computer Engineering

10. Mechanical Science & Engineering

11. Chemical and Biomolecular Engineering and Chemistry

12. Cancer Center at Illinois

Abstract

Infrared spectroscopy combined with deep learning provide an automated and quantitative alternative to traditional histological examination.

Funder

U.S. National Library of Medicine

National Institute of Diabetes and Digestive and Kidney Diseases

National Institute of Biomedical Imaging and Bioengineering

Cancer Prevention and Research Institute of Texas

Agilent Technologies

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2019/AN/C8AN01495G

Reference57 articles.

1. Simultaneous cancer and tumor microenvironment subtyping using confocal infrared microscopy for all-digital molecular histopathology

2. Infrared spectroscopic imaging for histopathologic recognition

3. Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

4. Fast Infrared Chemical Imaging with a Quantum Cascade Laser

5. R. Bhargava and I. W.Levin , Spectrochemical analysis using infrared multichannel detectors , John Wiley & Sons , 2008

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