@inproceedings{30723c6b9d28413e972c378e65e284ec,
title = "Measuring intra- and inter-observer agreement in identifying and localizing structures in medical images",
abstract = "Inter- and intra-observer variability exists in any measurements made on medical images. There are two sources of variability. The first occurs when the observers identify and localize the object of interest, and the second happens when the observers make appropriate measurement on the object of interest. A number of statistical methods are available to quantify the degree of agreement between measurements made by different observers. However, little has been done to develop metrics for quantifying the variability in identifying and localizing the objects of interest prior to measurement. In this paper, we propose to use the complex wavelet structural similarity index (CW-SSIM) method to measure the variability in identifying and localizing structures on images. Performance comparisons using simulated images as well as real mammography images demonstrate the effectiveness and robustness of the CW-SSIM method.",
author = "Sampat, {Mehul P.} and Zhou Wang and Markey, {Mia K.} and Whitman, {Gary J.} and Stephens, {Tanya W.} and Bovik, {Alan C.}",
year = "2006",
doi = "10.1109/ICIP.2006.312367",
language = "English (US)",
isbn = "1424404819",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "81--84",
booktitle = "2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings",
note = "2006 IEEE International Conference on Image Processing, ICIP 2006 ; Conference date: 08-10-2006 Through 11-10-2006",
}