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      The Potential of Hybridising Interactive Eye Tracking Technology with Decision Support in Medical Image Interpretation

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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Eye tracking, education, learning, medical image interpretation

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          This paper explores the use and future of interactive eye tracking technology within medical image interpretation. Eye tracking technology gives us an insight into the process and approaches taken by a reporting clinician during image interpretation. Application of this technology with verbalisation of thought processes and artificial intelligence could progress education and image interpretation further.

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          Most cited references 8

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          Viewing another person's eye movements improves identification of pulmonary nodules in chest x-ray inspection.

          Double reading of chest x-rays is often used to ensure that fewer abnormalities are missed, but very little is known about how the search behavior of others affects observer performance. A series of experiments investigated whether radiographers benefit from knowing where another person looked for pulmonary nodules, and whether the expertise of the model providing the search behavior was a contributing factor. Experiment 1 compared the diagnostic performance of novice and experienced radiographers examining chest x-rays and found that both groups performed better when shown the search behavior of either a novice radiographer or an expert radiologist. Experiment 2 established that benefits in performance only arose when the eye movements shown were related to the search for nodules; however, only the novices' diagnostic performance consistently improved when shown the expert's search behavior. Experiment 3 reexamined the contribution of task, image, and the expertise of the model underlying this benefit. Consistent with Experiment 1, novice radiographers were better at identifying nodules when shown either a naïve's search behavior or an expert radiologist's search behavior, but they demonstrated no improvement when shown a naïve model not searching for nodules. Our results suggest that although the benefits of this form of attentional guidance may be short-lived, novices can scaffold their decisions based on the search behavior of others. PsycINFO Database Record (c) 2010 APA, all rights reserved.
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            Missed lung cancer: when, where, and why?

            Missed lung cancer is a source of concern among radiologists and an important medicolegal challenge. In 90% of the cases, errors in diagnosis of lung cancer occur on chest radiographs. It may be challenging for radiologists to distinguish a lung lesion from bones, pulmonary vessels, mediastinal structures, and other complex anatomical structures on chest radiographs. Nevertheless, lung cancer can also be overlooked on computed tomography (CT) scans, regardless of the context, either if a clinical or radiologic suspect exists or for other reasons. Awareness of the possible causes of overlooking a pulmonary lesion can give radiologists a chance to reduce the occurrence of this eventuality. Various factors contribute to a misdiagnosis of lung cancer on chest radiographs and on CT, often very similar in nature to each other. Observer error is the most significant one and comprises scanning error, recognition error, decision-making error, and satisfaction of search. Tumor characteristics such as lesion size, conspicuity, and location are also crucial in this context. Even technical aspects can contribute to the probability of skipping lung cancer, including image quality and patient positioning and movement. Albeit it is hard to remove missed lung cancer completely, strategies to reduce observer error and methods to improve technique and automated detection may be valuable in reducing its likelihood.
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              Collaborative eye tracking: a potential training tool in laparoscopic surgery.

              Eye-tracking technology has been shown to improve trainee performance in the aircraft industry, radiology, and surgery. The ability to track the point-of-regard of a supervisor and reflect this onto a subjects' laparoscopic screen to aid instruction of a simulated task is attractive, in particular when considering the multilingual make up of modern surgical teams and the development of collaborative surgical techniques. We tried to develop a bespoke interface to project a supervisors' point-of-regard onto a subjects' laparoscopic screen and to investigate whether using the supervisor's eye-gaze could be used as a tool to aid the identification of a target during a surgical-simulated task. We developed software to project a supervisors' point-of-regard onto a subjects' screen whilst undertaking surgically related laparoscopic tasks. Twenty-eight subjects with varying levels of operative experience and proficiency in English undertook a series of surgically minded laparoscopic tasks. Subjects were instructed with verbal queues (V), a cursor reflecting supervisor's eye-gaze (E), or both (VE). Performance metrics included time to complete tasks, eye-gaze latency, and number of errors. Completion times and number of errors were significantly reduced when eye-gaze instruction was employed (VE, E). In addition, the time taken for the subject to correctly focus on the target (latency) was significantly reduced. We have successfully demonstrated the effectiveness of a novel framework to enable a supervisor eye-gaze to be projected onto a trainee's laparoscopic screen. Furthermore, we have shown that utilizing eye-tracking technology to provide visual instruction improves completion times and reduces errors in a simulated environment. Although this technology requires significant development, the potential applications are wide-ranging.

                Author and article information

                July 2018
                July 2018
                : 1-4
                Ulster University

                Northern Ireland
                NHS Greater Glasgow and Clyde

                © McLaughlin et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page):
                Electronic Workshops in Computing


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