Modeling decision-making in single- and multi-modal medical images

R. L. Canosa; K. G. Baum

doi:10.1117/12.811053

12 March 2009 Modeling decision-making in single- and multi-modal medical images

R. L. Canosa, K. G. Baum

Proceedings Volume 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment; 72630J (2009) https://doi.org/10.1117/12.811053
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

This research introduces a mode-specific model of visual saliency that can be used to highlight likely lesion locations and potential errors (false positives and false negatives) in single-mode PET and MRI images and multi-modal fused PET/MRI images. Fused-modality digital images are a relatively recent technological improvement in medical imaging; therefore, a novel component of this research is to characterize the perceptual response to these fused images. Three different fusion techniques were compared to single-mode displays in terms of observer error rates using synthetic human brain images generated from an anthropomorphic phantom. An eye-tracking experiment was performed with naïve (non-radiologist) observers who viewed the single- and multi-modal images. The eye-tracking data allowed the errors to be classified into four categories: false positives, search errors (false negatives never fixated), recognition errors (false negatives fixated less than 350 milliseconds), and decision errors (false negatives fixated greater than 350 milliseconds). A saliency model consisting of a set of differentially weighted low-level feature maps is derived from the known error and ground truth locations extracted from a subset of the test images for each modality. The saliency model shows that lesion and error locations attract visual attention according to low-level image features such as color, luminance, and texture.

Citation Download Citation

R. L. Canosa and K. G. Baum "Modeling decision-making in single- and multi-modal medical images", Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 72630J (12 March 2009); https://doi.org/10.1117/12.811053

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

Includes PDF, HTML & Video, when available