Gaze tracking for human-ultrasound machine interaction and medical image understanding
department or school: Applied Science, Faculty of
department or school: Biomedical Engineering, School of
data provider: DSpace
degree campus: UBCV
creator: Zhu, Hongzhi
issued: 2022-08-30T20:12:10Z
issued: 2022
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Despite the rapid advancement in medical imaging technologies, health care systems in Canada as well as in many other countries still cannot provide patients with sufficient medical imaging resources due to the ever-growing demands, lack of imaging devices, and fully trained medical practitioners. What makes the situation worse are persistent and prevalent work-related injury situations for medical practitioners, especially sonographers. To help these problems, the overall objective of this thesis is to improve the user interface design for ultrasound machines and contribute to automated medical imaging-based diagnosis with the help of the gaze tracking technology. Multi-themed study and research were conducted to achieve the objectives. On one hand, for the interface design improvement, we started by analyzing the characteristics of gaze signals through statistical modelling. Then we surveyed among sonographers to understand their daily usage of the ultrasound machines. Also, we analyzed different kinds of ultrasound machines to understand common design patterns and suboptimal control logic. To improve the suboptimal control logic and observed usage difficulties on ultrasound machines, we designed and implemented a gaze tracking contingent ultrasound machine. For the validation of our design ideas and machine effectiveness, comparative user studies were conducted. Additionally, we enhanced the user experience by solving the gaze tracker accuracy deterioration problem during normal usage of the devices by proposing a disruption-free auto-recalibration method. On the other hand, for the automated medical image diagnosis, with the integration of the gaze tracking dataset, we proposed deep learning methods that not only can provide a label that predicts which kind of abnormality is observed in the medical image, but also some reasoning that can guide humans to understand how the prediction is made. Multi-task learning methods and neural network attention mechanisms wer…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/82602
note: Gaze Tracking for Human-Ultrasound Machine Interaction andMedical Image UnderstandingbyHongzhi ZhuB.Eng., Tianjin University, 2014M.Eng., McGill University, 2017A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFDoctor of PhilosophyinTHE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Biomedical Engineering)The University of British Columbia(Vancouver)August 2022© Hongzhi Zhu, 2022The following individuals certify that they have read, and recommend to the Faculty of Graduateand Postdoctoral Studies for acceptance, the thesis entitled:Gaze Tracking for Human-Ultrasound Machine Interaction and Medical ImageUnderstandingsubmitted by Hongzhi Zhu in partial fulfillment of the requirements for the degree of Doctorof Philosophy in Biomedical Engineering.Examining Committee:Professor Robert Rohling, Electrical and Computer Engineering, Mechanical Engineering, andBiomedical Engineering, UBCCo-SupervisorProfessor Septimiu Salcudean, Electrical and Computer Engineering, and Biomedical Engineer-ing, UBCCo-SupervisorProfessor Jane Wang, Electrical and Computer Engineering, UBCSupervisory Committee MemberAssistant Professor Lyndia Wu, Mechanical Engineering, UBCSupervisory Committee MemberProfessor Terry Peters, Robarts Research Institute, Western UniversityExternal examinerProfessor Alla Sheffer, Computer Science, UBCUniversity examinerAssociate Professor Miriam Spering, Ophthalmology and Visual Sciences, UBCUniversity examineriiAbstractDespite the rapid advancement in medical imaging technologies, health care systems in Canadaas well as in many other countries still cannot provide patients with sufficient medical imagingresources due to the ever-growing demands, lack of imaging devices, and fully trained medicalpractitioners. What makes the situation worse are persistent and prevalent work-related injurysituations for medical practitioners, especially sonographers. To help these problems, the over-all objective of this thesis is to improve the user inter…
has type: Thesis/Dissertation
date issued: 2022-11
is shown at: 10.14288/1.0418439
language: eng
degree discipline: Biomedical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-ShareAlike 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-sa/4.0/
scholar level: Graduate
contributor: Rohling, Robert N.
contributor: Salcudean, Septimiu Edmund
type: Text
identifier URI: http://hdl.handle.net/2429/82602