Abstract
Assessment of medical image quality and how changes in image appearance impact performance are critical but assessment can be expensive and time-consuming. Could an animal (pigeon) observer with well-known visual skills and documented ability to distinguish complex visual stimuli serve as a surrogate for the human observer? Using sets of whole slide pathology (WSI) and mammographic images we trained pigeons (cohorts of 4) to detect and/or classify lesions in medical images. Standard training methods were used. A chamber equipped with a 15' display with a resistive touchscreen was used to display the images and record responses (pecks). Pigeon pellets were dispensed for correct responses. The pigeons readily learned to distinguish benign from malignant breast cancer histopathology in WSI (mean % correct responses rose 50% to 85% over 15 days) and generalized readily from 4X to 10X and 20X magnifications; to detect microcalcifications (mean % correct responses rose 50% to over 85% over 25 days); to distinguish benign from malignant breast masses (3 of 4 birds learned this task to around 80% and 60% over 10 days); and ignore compression artifacts in WSI (performance with uncompressed slides averaged 95% correct; 15:1 and 27:1 compression slides averaged 92% and 90% correct). Pigeons models may help us better understand medical image perception and may be useful in quality assessment by serving as surrogate observers for certain types of studies.
| Original language | English (US) |
|---|---|
| Title of host publication | Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment |
| Publisher | SPIE |
| Volume | 9787 |
| ISBN (Electronic) | 9781510600225 |
| DOIs | |
| State | Published - 2016 |
| Event | Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment - San Diego, United States Duration: Mar 2 2016 → Mar 3 2016 |
Other
| Other | Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment |
|---|---|
| Country | United States |
| City | San Diego |
| Period | 3/2/16 → 3/3/16 |
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Keywords
- Mammography
- Observer studies
- Pathology
- Performance
- Pigeons
- Visual perception
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Radiology Nuclear Medicine and imaging
Cite this
The potential of pigeons as surrogate observers in medical image perception studies. / Krupinski, Elizabeth A.; Levenson, Richard M; Navarro, Victor; Wasserman, Edward A.
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment. Vol. 9787 SPIE, 2016. 97870J.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - The potential of pigeons as surrogate observers in medical image perception studies
AU - Krupinski, Elizabeth A.
AU - Levenson, Richard M
AU - Navarro, Victor
AU - Wasserman, Edward A.
PY - 2016
Y1 - 2016
N2 - Assessment of medical image quality and how changes in image appearance impact performance are critical but assessment can be expensive and time-consuming. Could an animal (pigeon) observer with well-known visual skills and documented ability to distinguish complex visual stimuli serve as a surrogate for the human observer? Using sets of whole slide pathology (WSI) and mammographic images we trained pigeons (cohorts of 4) to detect and/or classify lesions in medical images. Standard training methods were used. A chamber equipped with a 15' display with a resistive touchscreen was used to display the images and record responses (pecks). Pigeon pellets were dispensed for correct responses. The pigeons readily learned to distinguish benign from malignant breast cancer histopathology in WSI (mean % correct responses rose 50% to 85% over 15 days) and generalized readily from 4X to 10X and 20X magnifications; to detect microcalcifications (mean % correct responses rose 50% to over 85% over 25 days); to distinguish benign from malignant breast masses (3 of 4 birds learned this task to around 80% and 60% over 10 days); and ignore compression artifacts in WSI (performance with uncompressed slides averaged 95% correct; 15:1 and 27:1 compression slides averaged 92% and 90% correct). Pigeons models may help us better understand medical image perception and may be useful in quality assessment by serving as surrogate observers for certain types of studies.
AB - Assessment of medical image quality and how changes in image appearance impact performance are critical but assessment can be expensive and time-consuming. Could an animal (pigeon) observer with well-known visual skills and documented ability to distinguish complex visual stimuli serve as a surrogate for the human observer? Using sets of whole slide pathology (WSI) and mammographic images we trained pigeons (cohorts of 4) to detect and/or classify lesions in medical images. Standard training methods were used. A chamber equipped with a 15' display with a resistive touchscreen was used to display the images and record responses (pecks). Pigeon pellets were dispensed for correct responses. The pigeons readily learned to distinguish benign from malignant breast cancer histopathology in WSI (mean % correct responses rose 50% to 85% over 15 days) and generalized readily from 4X to 10X and 20X magnifications; to detect microcalcifications (mean % correct responses rose 50% to over 85% over 25 days); to distinguish benign from malignant breast masses (3 of 4 birds learned this task to around 80% and 60% over 10 days); and ignore compression artifacts in WSI (performance with uncompressed slides averaged 95% correct; 15:1 and 27:1 compression slides averaged 92% and 90% correct). Pigeons models may help us better understand medical image perception and may be useful in quality assessment by serving as surrogate observers for certain types of studies.
KW - Mammography
KW - Observer studies
KW - Pathology
KW - Performance
KW - Pigeons
KW - Visual perception
UR - http://www.scopus.com/inward/record.url?scp=84976274663&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84976274663&partnerID=8YFLogxK
U2 - 10.1117/12.2207774
DO - 10.1117/12.2207774
M3 - Conference contribution
VL - 9787
BT - Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment
PB - SPIE
ER -