Title :
Improvement of sensitivity of breast cancer diagnosis with adaptive neighborhood contrast enhancement of mammograms
Author :
Rangayyan, Rangaraj M. ; Shen, Liang ; Shen, Yiping ; Desautels, J. E Leo ; Bryant, Heather ; Terry, Timothy J. ; Horeczko, Natalka ; Rose, M. Sarah
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Abstract :
Mammograms are difficult to interpret, especially of cancers at their early stages. We analyze the effectiveness of our adaptive neighborhood contrast enhancement (ANCE) technique in increasing the sensitivity of breast cancer diagnosis. Seventy-eight screen-film mammograms of 21 difficult cases (14 benign and seven malignant), 222 screen-film mammograms of 28 interval cancer patients and six benign control cases were digitized with a high-resolution of about 4096×2048×10-bit pixels and then processed with the ANCE method. Unprocessed and processed digitized mammograms as well as the original films were presented to six experienced radiologists for a receiver operating characteristic (ROC) evaluation for the difficult case set and to three reference radiologists for the interval cancer set. The results show that the radiologists´ performance with the ANCE-processed images is the best among the three sets of images (original, digitized, and enhanced) in terms of area under the ROC curve and that diagnostic sensitivity is improved by the ANCE algorithm. All of the 19 interval cancer cases not detected with the original films of earlier mammographic examinations were diagnosed as malignant with the corresponding ANCE-processed versions, while only one of the six benign cases initially labeled correctly with the original mammograms was interpreted as malignant after enhancement. This study demonstrates the potential for improvement of diagnostic performance in early detection of breast cancer with digital image enhancement.
Keywords :
diagnostic radiography; image enhancement; image resolution; medical image processing; statistical analysis; ANCE method; ROC evaluation; adaptive neighborhood contrast enhancement; breast cancer diagnosis; cancer patients; diagnostic sensitivity; digital image enhancement; image resolution; interval cancer; mammograms; pixels; radiologist performance; receiver operating characteristic evaluation; Biomedical imaging; Breast cancer; Cancer detection; Digital images; Image analysis; Image processing; Mammography; Medical diagnostic imaging; Sensitivity; Testing; Breast Neoplasms; Case-Control Studies; Female; Humans; Mammography; ROC Curve; Radiographic Image Interpretation, Computer-Assisted; Sensitivity and Specificity;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/4233.654859