Classification of breast abnormalities under different detection cueing environments

Bin Zheng; Richard G. Swensson; Amy H. Klym; Lara A. Hardesty; Ratan Shah; Luisa Wallace; Christiane M. Hakim; David Gur

doi:10.1117/12.533805

4 May 2004 Classification of breast abnormalities under different detection cueing environments

Bin Zheng, Richard G. Swensson, Amy H. Klym, Lara A. Hardesty, Ratan Shah, Luisa Wallace, Christiane M. Hakim, David Gur

Author Affiliations +

Proceedings Volume 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment; (2004) https://doi.org/10.1117/12.533805
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Eight radiologists interpreted 110 subtle cases in an observer performance study. The database includes 51 verified masses and 44 microcalcification clusters. Of these, 35 masses and 29 clusters were associated with malignancy. Two computer-aided detection (CAD) cueing conditions involving the same case-based sensitivity of 73% and two false-positive rates (0.8 or 2 per image) were applied. In each condition, radiologists interpreted 110 cases twice. In one reading mode radiologists first interpreted images without viewing CAD cues and then they could revise their initial interpretation after reviewing CAD cues. In another reading mode, radiologists viewed cues as soon as the images were displayed. Abnormalities were first detected by the radiologists and then classified as benign or malignant. The results demonstrated that these two cueing modes had little impact on radiologists performance after they have already made initial interpretation. However, displaying a large number of false-positive cues simultaneously with the images significantly reduced radiologists' performance in the classification of masses (p < 0.05). As false-positive cueing rate decreased the negative effect on classification performance decreased as well. Hence, inappropriate use of or reliance on CAD results with high false-positive rate could interfere with radiologists' attention to the classification task.

Citation Download Citation

Bin Zheng, Richard G. Swensson, Amy H. Klym, Lara A. Hardesty, Ratan Shah, Luisa Wallace, Christiane M. Hakim, and David Gur "Classification of breast abnormalities under different detection cueing environments", Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); https://doi.org/10.1117/12.533805

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE