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

This paper extends basic concepts of statistical hypothesis testing and confidence 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 used in the image reconstruction process, confidence maps for statistical tests on individual pixels and confidence intervals for entire images are displayed as an aid to research and clinical personnel interpreting possibly noisy images. The methods are applied to simulated and phantom-based images.