Mr. Mitchell Searjeant Profile

Mitchell Searjeant

at Univ of Nottingham

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Publications (3)

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SPIE Journal Paper | 9 May 2022

Digital pathology: the effect of experience on visual search behavior

Ellhia Sudin, Mitchell Searjeant, George Partridge, Peter Phillips, Louise Hiller, David R. Snead, Ian Ellis, Yan Chen

JMI, Vol. 9, Issue 03, 035501, (May 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.3.035501

KEYWORDS: Pathology, Visualization, Diagnostics, Eye, Digital imaging, Breast, Zoom lenses, Cameras, Statistical analysis, Core needle biopsy

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Purpose: The introduction of whole slide imaging and digital pathology has enabled greater scrutiny of visual search behaviors among pathologists. We aim to investigate zooming and panning behaviors, external markers of visual processing capabilities, and the changes with experience. Approaches: Twenty digitized breast core needle biopsy histopathology slides were obtained from the circulating slides from the main digital pathology trial (IRAS number: 258799). These were presented to five pathologists with varying experience (1.5 to 40 years) whose examinations were recorded. Data of visual fixations were collected using eye-tracking cameras, and the magnification data and zooming behaviors were extracted in an objective fashion by an automated algorithm. The relationship between experience and metrics was analyzed using mixed-effects regression analyses. Results: There was a significant association between experience and both reading times (p < 0.001) and a number of fixations (p < 0.001), with these relationships being inversely proportional. The greater experience was also associated with greater diagnostic accuracy (p = 0.033). We found that experience was significantly associated with greater use of magnification changes (p < 0.001). Conversely, less experience showed a near significant association with the increased proportion of time spent panning (p = 0.070). Conclusions: Fewer fixations needed to reach a diagnosis and quicker reading times are indicative of greater cognitive and visual processing capabilities with greater experience. These cognitive capabilities may be a prerequisite for the more frequent zooming changes that are more prevalent with increasing experience.

Proceedings Article | 15 February 2021 Presentation + Paper

Blink identification with eye tracking: a software processing program

Mitchell Searjeant, Peter Phillips, Dorina Roy, Alastair Gale, Yan Chen

Proceedings Volume 11599, 115990S (2021) https://doi.org/10.1117/12.2580967

KEYWORDS: Eye, Digital breast tomosynthesis, Digital mammography, Breast cancer

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Currently in the UK, a national trial to test the effect of a transition from traditional Full Field Digital Mammography (FFDM) to Digital Breast Tomosynthesis (DBT) is being conducted. DBT, having a higher sensitivity and specificity as compared to FFDM alone, could be a better modality in national breast cancer screening. However, its incorporation in the incredibly busy and detailed UK screening program is difficult. Reading times in DBT have been shown to be longer and strenuous (Connor et al, 2012). Therefore, much research needs to be completed to develop recommendations for its efficiency. One key factor in DBT reading is the progression of fatigue, as both a cause and effect of prolonged reading times. We aimed to develop a program to process real time raw eye tracking data to identify a change in fatigue-state through blink detection. Our focus was on analysing the whole data set and defining blinks through observed events. Two real time signals which the eye tracker generates, namely the left and right ‘Eyelid Opening’ value, were considered. Through assessment of these signals, blinks of varying duration were identified. Additional parameters such as recorded frame sequences and time stamps were added to the processing to delineate the exact occurrence of these blinks during the reading process. We aim to analyse past and future large DBT eye tracked files, with our processing software, to identify the point of fatigue onset in a DBT reading session.

Proceedings Article | 15 February 2021 Presentation + Paper

Employing eye tracking to identify the onset of fatigue in Digital Breast Tomosynthesis (DBT) readers for a national breast cancer screening programme

Dorina Roy, Amanda Koh, Alastair Gale, Peter Phillips, William Teh, Michael Michell, Nisha Sharma, Iain Darker, Mitchell Searjeant, Ellhia Sudin, Yan Chen

Proceedings Volume 11599, 115990T (2021) https://doi.org/10.1117/12.2580968

KEYWORDS: Digital breast tomosynthesis, Breast cancer, Eye, Pathology, Digital mammography

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The UK national screening program for breast cancer currently uses Full Field Digital Mammography (FFDM). Various studies have shown that DBT has a higher sensitivity and specificity in identifying early breast cancer apart from benign pathologies, even in very dense breasts. This potentially makes DBT a better screening modality to detect early breast cancer, as well as minimize false positive recall rates. However, DBT has multiple image slices and thereby makes reading cases inherently a longer and potentially more visually fatiguing task. Our previous studies (Dong et al, 2017 and 2018) have demonstrated the impact of institutional training on reading techniques in DBT. The reading technique itself appears to have an effect on total reading time. In other follow-on studies we have employed eye tracking which gives rise to complex data sets, including parameters such as eyelid opening and pupil diameter measures, which can then be employed to gauge blinks and fatigue onset. Findings from this work have guided changes in our blink identification techniques and we have now developed semi-automated programmed processes which can analyze the large data set and provide a more accurate assessment of fatigue and vigilance parameters through blink detection. Here, we have considered ‘eyelid opening’ parameters of both the left and the right eye separately. Having such a separated approach allowed us to tease out particular aspects of blinking. Similar to Schleicher et al (2008), we found there to be ultra-short blinks (30-50 milli seconds), short blinks (51- 100 msecs), long blinks (101-500 msecs) and also microsleeps (>500 msecs). We argue that the changes observed in the frequencies of these blinks can be used as a measure of vigilance and fatigue during DBT reading.

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