The perception of breast cancers-a spatial frequency analysis of what differentiates missed from reported cancers

Abstract

The primary detector of breast cancer is the human eye. Radiologists read mammograms by mapping exogenous and endogenous factors, which are based on the image and observer, respectively, into observer-based decisions. These decisions rely on an internal schema that contains a representation of possible malignant and benign findings. Thus, to understand the hits and misses made by the radiologists, it is important to model the interactions between the measurable image-based elements contained in the mammogram and the decisions made. The image-based elements can be of two types, i.e., areas that attracted the visual attention of the radiologist, but did not yield a report, and areas where the radiologist indicated the presence of an abnormal finding. In this way, overt and covert decisions are made when reading a mammogram. In order to model this decision-making process, we use a system that is based upon the processing done by the human visual system, which decomposes the areas under scrutiny in elements of different sizes and orientations. In our system, this decomposition is done using wavelet packets (WPs). Nonlinear features are then extracted from the WP coefficients, and an artificial neural network is trained to recognize the patterns of decisions made by each radiologist. Afterwards, the system is used to predict how the radiologist will respond to visually selected areas in new mammogram cases.

Spatial Localization Accuracy of Radiologists in Free-Response Studies: Inferring Perceptual FROC Curves from Mark-Rating Data

“…Nine (9) observers participated in the observer study, which was part of a larger study involving eye-position recordings (36). Three were experienced dedicated mammographers with at least 3 years experience reading mammograms, from the Department of Radiology, University of Pennsylvania, and six were radiology residents undergoing mammography rotation.…”

On the choice of acceptance radius in free-response observer performance studies

“…The assumption is that if the reader marks a location within this 2.5 u radius from the centre of the lesion, the lesion has been perceived. This method has been used by Mello-Thoms et al [15,16] in studies of detection of mammographic masses. One difficulty with this method is that the physical distance encompassed by any particular visual angle changes depending on how far away the eye is from the target.…”

“…In another study, MelloThoms et al [16] used an eye-to-monitor distance of 38 cm, which would give a slightly larger distance on the monitor screen. If the visual angle were used to calculate the acceptance radius in an experiment in which readers were free to choose any position from which to view the display or in which readers could adjust the apparent physical size of the image and lesion by zooming in on the image on a computer monitor, the calculated distance theoretically subsumed by this visual angle might have relatively little relationship to actual distance covered by the 2.5 u visual angle at the moment a suspected mass was identified or marked.…”

A Review of Research Into the Development of Radiologic Expertise: Implications for Computer-Based Training

“…High spatial frequencies correspond to fine detail, lower spatial frequencies to coarser elements.) Mello-Thoms, Dunn, Nodine and Kundel measured the log of the energy (energy being the integral of the signal strength) of different spatial frequency bands across a range of orientations, for each region fixated by a radiologist [45]. The profile of the log-energy measurements is obtained for each fixated region, this profile contains the information that we believe is computed by the low level visual system.…”