EconPapers    
Economics at your fingertips  
 

Online domain adaptation for continuous cross-subject liver viability evaluation based on irregular thermal data

Sahand Hajifar and Hongyue Sun

IISE Transactions, 2022, vol. 54, issue 9, 869-880

Abstract: Accurate evaluation of liver viability during its procurement is a challenging issue and has traditionally been addressed by taking an invasive biopsy of the liver. Recently, people have started to investigate the non-invasive evaluation of liver viability during its procurement using liver surface thermal images. However, existing works include the background noise in the thermal images and do not consider the cross-subject heterogeneity of livers, thus the viability evaluation accuracy can be affected. In this article, we propose to use the irregular thermal data of the pure liver region, and the cross-subject liver evaluation information (i.e., the available viability label information in cross-subject livers), for the real-time evaluation of a new liver’s viability. To achieve this objective, we extract features of irregular thermal data based on tools from Graph Signal Processing (GSP), and propose an online Domain Adaptation (DA) and classification framework using the GSP features of cross-subject livers. A multiconvex block coordinate descent-based algorithm is designed to jointly learn the domain-invariant features during online DA and the classifier. Our proposed framework is applied to the liver procurement data, and classifies the liver viability accurately.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2021.1949762 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:54:y:2022:i:9:p:869-880

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/24725854.2021.1949762

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:uiiexx:v:54:y:2022:i:9:p:869-880