Deep learning based on co-registered ultrasound and photoacoustic imaging improves the assessment of rectal cancer treatment response

Authors

Yixiao Lin, Washington University in St. Louis
Sitai Kou, Washington University in St. Louis
Haolin Nie, Washington University in St. Louis
Hongbo Luo, Washington University in St. Louis
Ahmed Eltahir, Washington University School of Medicine in St. Louis
Will Chapman Jr., Washington University School of Medicine in St. Louis
Steven Hunt, Washington University School of Medicine in St. Louis
Matthew Mutch, Washington University School of Medicine in St. Louis
Quing Zhu, Washington University School of Medicine in St. Louis

Journal

Biomedical Optical Express

Publication Date

5-1-2023

Volume

14

Issue

5

First Page

2015

Last Page

2027

Document Type

Open Access Publication

DOI

10.1364/BOE.487647

Rights and Permissions

Lin Y, Kou S, Nie H, Luo H, Eltahir A, Chapman W Jr, Hunt S, Mutch M, Zhu Q. Deep learning based on co-registered ultrasound and photoacoustic imaging improves the assessment of rectal cancer treatment response. Biomed Opt Express. 2023 Apr 13;14(5):2015-2027. doi: 10.1364/BOE.487647. Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Recommended Citation

Lin, Yixiao; Kou, Sitai; Nie, Haolin; Luo, Hongbo; Eltahir, Ahmed; Chapman, Will Jr.; Hunt, Steven; Mutch, Matthew; and Zhu, Quing, "Deep learning based on co-registered ultrasound and photoacoustic imaging improves the assessment of rectal cancer treatment response." Biomedical Optical Express. 14, 5. 2015 - 2027. (2023).
https://digitalcommons.wustl.edu/oa_4/2047

Department

ICTS (Institute of Clinical and Translational Sciences)

Additional Links

Supplemental material is available for this article at publisher site.