Confidence maps and confidence intervals for near infrared images in breast cancer

This paper extends basic concepts of statistical hypothesis testing and con fidence intervals to images generated by a new procedure for near infrared spectroscopic tomography being developed for use in breast cancer diagnosis . By estimating the covariance matrix of the pixels of an image from data u sed in the image reconstruction process, confidence maps for statistical te sts on individual pixels and confidence intervals for entire images are dis played as an aid to research and clinical personnel interpreting possibly n oisy images. The methods are applied to simulated and phantom-based images.