Recording and analyzing eye-position data using a microcomputer workstation

Nodine, Calvin F.; Kundel, Harold L.; Toto, Lawrence C.; Krupiński, Elizabeth A.

doi:10.3758/bf03203584

Cited by 82 publications

(28 citation statements)

References 16 publications

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“…It should be noted that in both the P+C and P conditions, detection was significantly lower for the outside than for the inside tumors, but as was noted previously, this was independent of whether or not a tumor had been reported in the inside zone. The lower detection rate probably had more to do with the fact that peripheral vision was required to detect the outside tumors (Nodine et al, 1992).…”

Section: Discussionmentioning

confidence: 99%

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Perceptual enhancement of tumor targets in chest X-ray images

Krupiński

Nodine

Kundel

1993

Perception & Psychophysics

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Under tachistoscopic viewing conditions, precuing the location of potential lung tumor targets in chest X-ray images was less effective than precuing followed by bounding the region of interest (ROI) with a circle directly on the image. Detection performance increased as the image was systematically masked so that its size approximated that of the circled ROt When viewing time was extended to allow shifts in eye position, circling the ROI was found to restrict the dispersion of fixations and increase the accuracy of fixating the target tumor. When targets were placed outside the ROI, the circle inhibited their detection relative to detection of targets inside the circled region. These findings suggest that cuing by circling restricts target detection to the ROI, and by doing so reduces the interfering effects of outside distractors that compete with the target for attention.In medical X-ray imaging, tumors of the lungs, breasts, and other major organs make up a major class of search and detection targets. The detection and recognition of these targets is especially difficult because of (1) the presence of numerous anatomical objects that also possess similar features (e.g., blood vessels on end in the lungs); and (2) camouflaging effects created by projection X-ray imaging techniques. Essentially, the observer is searching a two-dimensional, translucent picture of internal human anatomy created from the shadows of the absorption pattern of X-rays passing through the body to the film plate, and interpreting these patterns as three-dimensional objects. The magnitude of the difficulty of this particular search and detection task is evident when error rates in radiology are considered. Misses (false-negatives) of tumors, fractures, and other diagnostic findings can be as high as 30%, and false-positive rates typically run at 10%-15%

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Section: Discussionmentioning

confidence: 99%

“…On the average, search was terminated after 5 sec. Eye position was recorded (Eye-Trac Model 210; Applied Science Laboratories, Waltham, MA) according to a limbus-reflection technique (see Nodine, Kundel, Toto, & Krupinski, 1992, for complete details of the eye-position recording and analysis procedures).…”

Section: Methodsmentioning

confidence: 99%

Perceptual enhancement of tumor targets in chest X-ray images

Krupiński

Nodine

Kundel

1993

Perception & Psychophysics

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“…Methods of analysing the search pathways in medical images have been produced by Nodine and Kundel and Nodine at al. [28,29]. Nodine reported that the minimal dwell time for abnormality recognition of lung nodules is 900 ms and, with Kundel, provided a method to reduce the recognition failure of abnormal features [28].…”

Section: Discussionmentioning

confidence: 99%

Does Expectation of Abnormality Affect the Search Pattern of Radiologists When Looking for Pulmonary Nodules?

et al. 2016

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This experiment investigated whether there might be an effect on the visual search strategy of radiologists during image interpretation of the same adult chest radiographs when given different clinical information. Each of 17 experienced radiologists was asked to interpret a set of 57 (10 abnormal) posteroanterior chest images to identify the presence of pulmonary lesions using differing clinical information (leading to unknown, low and high expectations of prevalence). Eye position metrics (search time, dwell time and time to first fixation) were compared for normal and abnormal images, as well as between conditions. For all images, there was a significantly longer search time at high prevalence expectation compared to low prevalence expectation (W = 75.19, P = <0.0001). Mann-Whitney analysis of the abnormal images demonstrated that the dwell time on correctly identified lesions was significantly shorter at low prevalence expectation compared to both unknown (U = 364.5, P = 0.02) and high prevalence expectation (U = 397.0, P = 0.0002). Visual search patterns of radiologists appear to be affected by changing a priori information where such information fosters an expectation of abnormality.

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“…True-negative decision dwell time is calculated from image regions that are lesion free but receive fixation clusters. 114 Higher display luminance, 115 calibration with the Digital Imaging and Communications in Medicine ͑DICOM͒ Grayscale Display Function standard, 116 high-performance monochrome rather than color display, 117 and 11-bit rather than 8-bit display 118 all result in higher search efficiency and improved diagnostic accuracy. Even the graphical user interface ͑GUI͒ and the way in which images and tool bars are positioned on the display can affect search efficiency.…”

Section: Evaluation Of Other Human Factors That Affect Diagnosticmentioning

confidence: 99%

Anniversary Paper: Evaluation of medical imaging systems

Krupiński

Jiang

2008

Med. Phys.

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Medical imaging used to be primarily within the domain of radiology, but with the advent of virtual pathology slides and telemedicine, imaging technology is expanding in the healthcare enterprise. As new imaging technologies are developed, they must be evaluated to assess the impact and benefit on patient care. The authors review the hierarchical model of the efficacy of diagnostic imaging systems by Fryback and Thornbury ͓Med. Decis. Making 11, 88-94 ͑1991͔͒ as a guiding principle for system evaluation. Evaluation of medical imaging systems encompasses everything from the hardware and software used to acquire, store, and transmit images to the presentation of images to the interpreting clinician. Evaluation of medical imaging systems can take many forms, from the purely technical ͑e.g., patient dose measurement͒ to the increasingly complex ͑e.g., determining whether a new imaging method saves lives and benefits society͒. Evaluation methodologies cover a broad range, from receiver operating characteristic ͑ROC͒ techniques that measure diagnostic accuracy to timing studies that measure image-interpretation workflow efficiency. The authors review briefly the history of the development of evaluation methodologies and review ROC methodology as well as other types of evaluation methods. They discuss unique challenges in system evaluation that face the imaging community today and opportunities for future advances.

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Recording and analyzing eye-position data using a microcomputer workstation

Cited by 82 publications

References 16 publications

Perceptual enhancement of tumor targets in chest X-ray images

Perceptual enhancement of tumor targets in chest X-ray images

Does Expectation of Abnormality Affect the Search Pattern of Radiologists When Looking for Pulmonary Nodules?

Anniversary Paper: Evaluation of medical imaging systems

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