» Articles » PMID: 9419461

Searching for Bone Fractures: a Comparison with Pulmonary Nodule Search

Overview
Journal Acad Radiol
Specialty Radiology
Date 1994 Sep 1
PMID 9419461
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

Rationale And Objectives: We aimed to determine if the characteristics and principles of visual search described for the detection of pulmonary nodules apply to extremity fractures.

Methods: The eye positions of staff orthopedic radiologists, radiology residents, and medical students were monitored as they searched hand and wrist X-ray images for fractures and a chest image for nodules.

Results: More systematic scanning patterns were observed for experienced observers than inexperienced observers. Positive decisions for bone images were associated with prolonged gaze durations; prolonged gaze durations were significantly longer for false-negative versus true-negative decisions. Intercluster jump distances were found to be greater for chest images than bone images.

Conclusions: A search for bone fractures can be qualitatively characterized by classifying observer scan paths, dwell times, and jump distances. Gaze duration can be a useful predictor of bone image locations containing potential missed fractures. Perceptual feedback could aid observers in the detection of inconspicuous fractures.

Citing Articles

Training focal lung pathology detection using an eye movement modeling example.

Brams S, Ziv G, Hooge I, Levin O, Verschakelen J, Williams A J Med Imaging (Bellingham). 2021; 8(2):025501.

PMID: 33732754 PMC: 7955141. DOI: 10.1117/1.JMI.8.2.025501.


Search of low-contrast liver lesions in abdominal CT: the importance of scrolling behavior.

Ba A, Shams M, Schmidt S, Eckstein M, Verdun F, Bochud F J Med Imaging (Bellingham). 2020; 7(4):045501.

PMID: 32743016 PMC: 7380560. DOI: 10.1117/1.JMI.7.4.045501.


Eye Movements in Medical Image Perception: A Selective Review of Past, Present and Future.

Wu C, Wolfe J Vision (Basel). 2019; 3(2).

PMID: 31735833 PMC: 6802791. DOI: 10.3390/vision3020032.


Eye Tracking for Deep Learning Segmentation Using Convolutional Neural Networks.

Stember J, Celik H, Krupinski E, Chang P, Mutasa S, Wood B J Digit Imaging. 2019; 32(4):597-604.

PMID: 31044392 PMC: 6646645. DOI: 10.1007/s10278-019-00220-4.


The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review.

Sheridan H, Reingold E Front Psychol. 2017; 8:1620.

PMID: 29033865 PMC: 5627012. DOI: 10.3389/fpsyg.2017.01620.