Using Gaze-tracking Data and Mixture Distribution Analysis to Support a Holistic Model for the Detection of Cancers on Mammograms

Rationale and Objectives: Use data collected independently at three institutions to compare time to first fixate the true lesion in searching for cancers on mammograms. Examine the fit of the results to a holistic model of visual perception. Materials and Methods: The time required to first fixate a cancer on a mammogram was extracted from 400 eye-tracking records collected independently from three institutions. The time was used as an indicator of the initial perception of cancer. The distribution of first fixation times was partitioned into two normally distributed components using mixture distribution analysis. The true-positive fraction of each component was calculated. Results: About 57% of the cancers had a 95% chance of being fixated in the first second of viewing. The remainder took longer (range, 1.0 to 15.2 seconds). The true-positive fraction was larger for the lesions hit immediately for most of the readers (TPF = 0.63 vs. 0.52, F = 5.88, P = .02) in 68% (13/19) of the readers. Conclusions: The initial detection occurs before visual scanning and, therefore, must be the result of a parallel "global" analysis of the image resulting in an initial holistic, gestalt-like perception. The development of expertise in medical image analysis may consist of a shift in the recognition mechanism from scan-look-detect to look-detect-scan.