The correlation of feature identification and category judgments in diagnostic radiology

Norman, Geoffrey R.; Brooks, Lee R.; Coblentz, Craig; Babcook, Catherine J.

doi:10.3758/bf03210919

Cited by 75 publications

(36 citation statements)

References 22 publications

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“…Moreover, clinical information led observers to make falsepositive diagnoses, which appeared consistent between observer ratings. Norman, Brooks, Coblentz and Babcock (1992) 18 investigated the overall effects of brief clinical history on the diagnosis and feature detection of bronchilitis and uncovered that both experts and novice readers were influenced by clinical information, although novices made more false-positive reports than experts on this feature detection task. Hobby et al (2000) 9 proposed that image assessments are heavily influenced by radiological reports and owing to mixed findings and lack of evidence surrounding the effect of information on image appraisal, confirmed clinical diagnosis and treatment outcome for the patient (e.g.…”

Section: The Effect Of Clinical Information On Medical Image Appraisalmentioning

confidence: 99%

Radiology image perception and observer performance: How does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking

et al. 2009

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Additional Information:• ABSTRACTHistorically, radiology research has been dominated by chest and breast screening. Few studies have examined complex interpretative tasks such as the reading of multidimensional brain CT or MRI scans. Additionally, no studies at the time of writing have explored the interpretation of stroke images; from novices through to experienced practitioners using eye movement analysis. Finally, there appears a lack of evidence on the clinical effects of radiology reports and their influence on image appraisal and clinical diagnosis. A computer-based, eye-tracking study was designed to assess diagnostic accuracy and interpretation in stroke CT and MR imagery. Eight predetermined clinical cases, five images per case, were presented to participants (novices, trainee, and radiologists; n=8). The presence or absence of abnormalities was rated on a five-point Likert scale and their locations reported. Half cases of the cases were accompanied by clinical information; half were not, to assess the impact of information on observer performance. Results highlight differences in visual search patterns amongst novice, trainee and expert observers; the most marked differences occurred between novice readers and experts. Experts spent more time in challenging areas of interest (AOI) than novices and trainee, and were more confident unless a lesion was large and obvious. The time to first AOI fixation differed by size, shape and clarity of lesion. 'Time to lesion' dropped significantly when recognition appeared to occur between slices. The influence of clinical information was minimal.

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Section: The Effect Of Clinical Information On Medical Image Appraisalmentioning

confidence: 99%

Radiology image perception and observer performance: How does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking

et al. 2009

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“…The medical expertise literature abounds with illustrations of category learning that do not seem to fit well with the idea that relevant cues are a given. For example, when complete novices categorize dermatosis (Norman et al, 1992), sex chicks (Biederman and Shiffrar, 1987) and read chest X-rays (Christensen et al, 1981;Lesgold, 1984) they are not always able to see the relevant cues of the stimuli. Expertise with these categories involves as much learning which cue goes with which categories as learning the object cues themselves.…”

Section: Example 2: Object Information and Categorizationmentioning

confidence: 99%

Diagnostic recognition: task constraints, object information, and their interactions

1998

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“…The case-based approach should teach the ability to connect clinical findings with imaging findings as an essential learning objective in radiology (27). Since it is generally difficult to evaluate learning success in problem-solving environments, we decided on a twofold testing scenario.…”

Section: Motivation and Learning Successmentioning

confidence: 99%

Do Computers Teach Better? A Media Comparison Study for Case-based Teaching in Radiology

Maleck

Fischer²,

Kammer³

et al. 2001

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A prospective study was performed to better define the role of computers in teaching radiology to medical students. Two hundred twentyfive 3rd-year students were randomly assigned to one of four groups and exposed to 10 radiology cases as well as to a voluntary weekly radiology lecture. Group A used computer-based cases with interactive elements; group B used computer-based cases without interactive elements; group C used paper-based cases with interactive elements; and group D was not exposed to the cases and served as a control group. On a multiple-choice question test, groups A, B, and C showed significant improvement (ϩ11.2%, ϩ15.1%, and ϩ13.0%, respectively), whereas group D did not (ϩ0.6%). On an image interpretation test, group A showed the most improvement (ϩ15.7% [P Ͻ .001]), followed by group B (ϩ15.1% [P Ͻ .01]) and group C (ϩ10.2% [P Ͻ .05]); group D showed no significant improvement (ϩ8.5%). No significant differences in the learning outcome were found between the two interactive groups (computer based and paper based). Computerbased teaching with case studies (with or without interactivity) improves students' problem-solving ability in radiology.

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The correlation of feature identification and category judgments in diagnostic radiology

Cited by 75 publications

References 22 publications

Radiology image perception and observer performance: How does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking

Radiology image perception and observer performance: How does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking

Diagnostic recognition: task constraints, object information, and their interactions

Do Computers Teach Better? A Media Comparison Study for Case-based Teaching in Radiology

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