Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan

Minxin Chen; Victor C. S. Lee; Brian Chin Wing Kot; María José Robles Malagamba

doi:10.1109/TENCON55691.2022.9977573

Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan

Minxin Chen, Victor C. S. Lee, Brian Chin Wing Kot, María José Robles Malagamba

Department of Infectious Diseases and Public Health

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Postmortem computed tomography (PMCT) scan has long been used in the postmortem examination of cetaceans on Virtopsy to find out the cause of death such as diseases on internal organs. However, manual diagnosis using PMCT scans is labour-intensive and time consuming. Driven by the recent advances in deep learning, in this project, we develop a computer-aided diagnosis system based on U-Net, a convolutional neural network, for cetaceans. In addition, we propose two loss functions to resolve the bias due to the skewed distribution of the different areas in the PMCT-scans, thereby improving the system accuracy significantly.

Original language	English
Title of host publication	2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration
Subtitle of host publication	“Tech-Biz Intelligence”
Publisher	IEEE
ISBN (Electronic)	978-1-6654-5095-9
DOIs	https://doi.org/10.1109/TENCON55691.2022.9977573
Publication status	Published - 2022
Event	2022 IEEE Region 10 International Conference, TENCON 2022 - Virtual, Online, Hong Kong, China Duration: 1 Nov 2022 → 4 Nov 2022 https://www.tencon2022.org/

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2022-November
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	2022 IEEE Region 10 International Conference, TENCON 2022
Place	Hong Kong, China
City	Virtual, Online
Period	1/11/22 → 4/11/22
Internet address	https://www.tencon2022.org/

Funding

This project is financially supported by CityU Strategic Research Grant; Marine Conservation Enhancement Fund; Marine Ecology Enhancement Fund; and Research Grants Council of the HKSAR, China (grant no.: CityU11102619, CityU11104721, CityU11104720, MCEF20007, MEEF2019010, MEEF2019010A, MEEF2019010B).

Research Keywords

cetaceans
loss function
segmentation
U-Net

RGC Funding Information

RGC-funded

Access Output

10.1109/TENCON55691.2022.9977573

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Chen, M., Lee, V. C. S., Kot, B. C. W., & Robles Malagamba, M. J. (2022). Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan. In 2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration: “Tech-Biz Intelligence” (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2022-November). IEEE. https://doi.org/10.1109/TENCON55691.2022.9977573

Chen, Minxin ; Lee, Victor C. S. ; Kot, Brian Chin Wing et al. / Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan. 2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration: “Tech-Biz Intelligence”. IEEE, 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

@inproceedings{fb82bcdccc3f4d209e67970ce1bc19f2,

title = "Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan",

abstract = "Postmortem computed tomography (PMCT) scan has long been used in the postmortem examination of cetaceans on Virtopsy to find out the cause of death such as diseases on internal organs. However, manual diagnosis using PMCT scans is labour-intensive and time consuming. Driven by the recent advances in deep learning, in this project, we develop a computer-aided diagnosis system based on U-Net, a convolutional neural network, for cetaceans. In addition, we propose two loss functions to resolve the bias due to the skewed distribution of the different areas in the PMCT-scans, thereby improving the system accuracy significantly.",

keywords = "cetaceans, loss function, segmentation, U-Net",

author = "Minxin Chen and Lee, {Victor C. S.} and Kot, {Brian Chin Wing} and {Robles Malagamba}, {Mar{\'i}a Jos{\'e}}",

year = "2022",

doi = "10.1109/TENCON55691.2022.9977573",

language = "English",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "IEEE",

booktitle = "2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration",

address = "United States",

note = "2022 IEEE Region 10 International Conference, TENCON 2022 ; Conference date: 01-11-2022 Through 04-11-2022",

url = "https://www.tencon2022.org/",

}

Chen, M, Lee, VCS , Kot, BCW & Robles Malagamba, MJ 2022, Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan. in 2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration: “Tech-Biz Intelligence”. IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2022-November, IEEE, 2022 IEEE Region 10 International Conference, TENCON 2022, Virtual, Online, Hong Kong, China, 1/11/22. https://doi.org/10.1109/TENCON55691.2022.9977573

Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan. / Chen, Minxin; Lee, Victor C. S.; Kot, Brian Chin Wing et al.
2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration: “Tech-Biz Intelligence”. IEEE, 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2022-November).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan

AU - Chen, Minxin

AU - Lee, Victor C. S.

AU - Kot, Brian Chin Wing

AU - Robles Malagamba, María José

PY - 2022

Y1 - 2022

N2 - Postmortem computed tomography (PMCT) scan has long been used in the postmortem examination of cetaceans on Virtopsy to find out the cause of death such as diseases on internal organs. However, manual diagnosis using PMCT scans is labour-intensive and time consuming. Driven by the recent advances in deep learning, in this project, we develop a computer-aided diagnosis system based on U-Net, a convolutional neural network, for cetaceans. In addition, we propose two loss functions to resolve the bias due to the skewed distribution of the different areas in the PMCT-scans, thereby improving the system accuracy significantly.

AB - Postmortem computed tomography (PMCT) scan has long been used in the postmortem examination of cetaceans on Virtopsy to find out the cause of death such as diseases on internal organs. However, manual diagnosis using PMCT scans is labour-intensive and time consuming. Driven by the recent advances in deep learning, in this project, we develop a computer-aided diagnosis system based on U-Net, a convolutional neural network, for cetaceans. In addition, we propose two loss functions to resolve the bias due to the skewed distribution of the different areas in the PMCT-scans, thereby improving the system accuracy significantly.

KW - cetaceans

KW - loss function

KW - segmentation

KW - U-Net

UR - http://www.scopus.com/inward/record.url?scp=85145654404&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85145654404&origin=recordpage

U2 - 10.1109/TENCON55691.2022.9977573

DO - 10.1109/TENCON55691.2022.9977573

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

BT - 2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration

PB - IEEE

T2 - 2022 IEEE Region 10 International Conference, TENCON 2022

Y2 - 1 November 2022 through 4 November 2022

ER -

Chen M, Lee VCS , Kot BCW , Robles Malagamba MJ. Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan. In 2022 IEEE TENCON - Proceedings of 2022 IEEE Region 10 International Conference cum IEEE Hong Kong 50th Anniversary Celebration: “Tech-Biz Intelligence”. IEEE. 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON). Epub 2022 Dec 20. doi: 10.1109/TENCON55691.2022.9977573

Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan

Abstract

Publication series

Conference

Funding

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

HKgovt: Three-dimensional Forensic Scene Investigation of Marine Vessel Interaction in Indo-Pacific Humpbacked Dolphins and Indo-Pacific Finless Porpoises in the Hong Kong Waters (Phase 3)

GRF: Core Habitat in a High Vessel Traffic Port: Risk Assessment and Mitigation on Marine Vessel Interaction for Cetaceans Residing in Hong Kong Waters

HKgovt: Three-Dimensional Forensic Scene Investigation of Marine Vessel Interaction in Indo-Pacific Humpbacked Dolphins and Indo-Pacific Finless Porpoises in the Hong Kong Waters (Phase 2)

Cite this

Enhanced U-Net for Computer-aided Diagnosis with Cetacean Postmortem CT Scan

Abstract

Publication series

Conference

Funding

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

HKgovt: Three-dimensional Forensic Scene Investigation of Marine Vessel Interaction in Indo-Pacific Humpbacked Dolphins and Indo-Pacific Finless Porpoises in the Hong Kong Waters (Phase 3)

GRF: Core Habitat in a High Vessel Traffic Port: Risk Assessment and Mitigation on Marine Vessel Interaction for Cetaceans Residing in Hong Kong Waters

HKgovt: Three-Dimensional Forensic Scene Investigation of Marine Vessel Interaction in Indo-Pacific Humpbacked Dolphins and Indo-Pacific Finless Porpoises in the Hong Kong Waters (Phase 2)

Cite this