Adaptation and the Perception of Radiological Images

Radiologists must classify and interpret medical images on the basis of visual inspection. We examined how an observer's visual sensitivity and perception might change as they view and thus adapt to the characteristic properties of radiological scans. Measurements were focused on the effects of adaptation to images of normal mammograms, and were tested primarily in observers who were not trained radiologists. Mammograms have steeper power spectra (slopes of ~-3) than natural images (~-2) and thus are physically blurry. Adapting to them produced shifts in the perceived spectrum of filtered noise consistent with adaptation to blur, even though this adaptation does not lead to measurable changes in the contrast sensitivity function. Strong aftereffects in the appearance of the images were also found when observers judged the perceived texture of the images. For example, tissue density in mammograms is routinely classified and ranges from "dense" to "fatty." Adaptation to dense images caused an intermediate image to appear more fatty and vice versa. Our results thus suggest that observers can selectively adapt to the properties of radiological images, and this could potentially be an important factor in the perception and learning of radiological images. In a further study we explored whether adaptation could enhance visual inspection of radiological images, specifically to aid observers in identifying abnormalities by adapting out or discounting the expected visual characteristics of the background. Observers searched for simulated lesions (Gaussian targets) added at random locations in the images. Prior adaptation to the images allowed the targets to be located more quickly, and this performance gain was selective for the tissue type and thus the visual texture defining the background. These improvements in visual search provide a novel demonstration of the advantages of spatial pattern adaptation within contexts that closely mimic routine visual tasks and settings. Finally, we explored the neural correlates of these adaptation aftereffects by measuring ERP's while observers adapted to the different textural properties of the mammogram images (dense or fatty). There was no significant difference of adapt condition in the component waveforms when tasked with categorizing the scans based upon their density classifications. In contrast, there was a significant effect of adaptation when observers were signaling target presence or absence. This significant difference was characterized by an enhancement of the neural response at early timepoints in occipital areas. Additionally, following adaptation we observed a divergence in the target present and absent waveforms at approximately 370 ms post-stimulus onset in frontal recording sites. These results suggest that target detection involves a form of the P300 component. Taken together these studies represent the first comprehensive analysis of the influence of adaption on the critically important visual judgments involved in interpreting and inspecting medical images. &#8195

Adaptation and visual search in mammographic images

Abstract Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the im-ages. The stimuli were randomly selected sections from nor-mal mammograms previously classified with BIRADS Den-sity scores of Bfatty ^ versus Bdense, ^ corresponding to differ-ences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in vi-sual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corre-sponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was random-ly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background tex-ture. Our results are consistent with the hypothesis that adap-tation allows observers to more effectively suppress the spe-cific structure of the background, thereby heightening visual salience and search efficiency

Visual adaptation and the amplitude spectra of radiological images.

We examined how visual sensitivity and perception are affected by adaptation to the characteristic amplitude spectra of X-ray mammography images. Because of the transmissive nature of X-ray photons, these images have relatively more low-frequency variability than natural images, a difference that is captured by a steeper slope of the amplitude spectrum (~ - 1.5) compared to the ~ 1/f (slope of - 1) spectra common to natural scenes. Radiologists inspecting these images are therefore exposed to a different balance of spectral components, and we measured how this exposure might alter spatial vision. Observers (who were not radiologists) were adapted to images of normal mammograms or the same images sharpened by filtering the amplitude spectra to shallower slopes. Prior adaptation to the original mammograms significantly biased judgments of image focus relative to the sharpened images, demonstrating that the images are sufficient to induce substantial after-effects. The adaptation also induced strong losses in threshold contrast sensitivity that were selective for lower spatial frequencies, though these losses were very similar to the threshold changes induced by the sharpened images. Visual search for targets (Gaussian blobs) added to the images was also not differentially affected by adaptation to the original or sharper images. These results complement our previous studies examining how observers adapt to the textural properties or phase spectra of mammograms. Like the phase spectrum, adaptation to the amplitude spectrum of mammograms alters spatial sensitivity and visual judgments about the images. However, unlike the phase spectrum, adaptation to the amplitude spectra did not confer a selective performance advantage relative to more natural spectra

Adaptation and visual search in mammographic images

Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the images. The stimuli were randomly selected sections from normal mammograms previously classified with BIRADS Density scores of "fatty" versus "dense," corresponding to differences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in visual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corresponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was randomly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background texture. Our results are consistent with the hypothesis that adaptation allows observers to more effectively suppress the specific structure of the background, thereby heightening visual salience and search efficiency

Visual adaptation and the amplitude spectra of radiological images

Abstract We examined how visual sensitivity and perception are affected by adaptation to the characteristic amplitude spectra of X-ray mammography images. Because of the transmissive nature of X-ray photons, these images have relatively more low-frequency variability than natural images, a difference that is captured by a steeper slope of the amplitude spectrum (~ − 1.5) compared to the ~ 1/f (slope of − 1) spectra common to natural scenes. Radiologists inspecting these images are therefore exposed to a different balance of spectral components, and we measured how this exposure might alter spatial vision. Observers (who were not radiologists) were adapted to images of normal mammograms or the same images sharpened by filtering the amplitude spectra to shallower slopes. Prior adaptation to the original mammograms significantly biased judgments of image focus relative to the sharpened images, demonstrating that the images are sufficient to induce substantial after-effects. The adaptation also induced strong losses in threshold contrast sensitivity that were selective for lower spatial frequencies, though these losses were very similar to the threshold changes induced by the sharpened images. Visual search for targets (Gaussian blobs) added to the images was also not differentially affected by adaptation to the original or sharper images. These results complement our previous studies examining how observers adapt to the textural properties or phase spectra of mammograms. Like the phase spectrum, adaptation to the amplitude spectrum of mammograms alters spatial sensitivity and visual judgments about the images. However, unlike the phase spectrum, adaptation to the amplitude spectra did not confer a selective performance advantage relative to more natural spectra

Additional file 1: of Visual adaptation and the amplitude spectra of radiological images

An animation illustrating blur after-effects in the images. The three adapting images with slopes of − 1.4, − 1.25, or − 1 are shown for 3 s, alternated with three test images all with the same slope of − 1.25 shown for 1 s. The after-effects are best experienced by continuously fixating the center image. The test images on the left and right should appear sharper and blurrier, respectively, relative to the central test image. (GIF 180kb