TY - GEN
T1 - STEP
T2 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
AU - Yuanjie, Zheng
AU - Englander, Sarah
AU - Schnall, Mitchell D.
AU - Dinggang, Shen
PY - 2007
Y1 - 2007
N2 - This paper demonstrates the importance of capturing SpatialTemporal Enhancement Pattern (STEP) for completely characterizing breast tumor in contrast-enhanced MR images. STEP captures not only the dynamic enhancement and architectural features of tumor, but also the spatial variations of pixel-wise temporal enhancement of tumor. Although the latter has been widely used by radiologist during diagnosis, it is rarely considered as important features for computer-aided tumor diagnosis. Notice that, by regarding serial contrast-enhanced images as a single spatial-temporal image, STEP can capture all types of the features within a single framework. In particular, a Fourier transformation is used to extract various temporal enhancement features, followed by moment invariants to capture spatial patterns of each temporal enhancement feature. Experimental results show the better performance of our designed STEP features than many other features available in the literature. The area under ROC curve can reach 0.96 with our STEP features in tumor diagnosis.
AB - This paper demonstrates the importance of capturing SpatialTemporal Enhancement Pattern (STEP) for completely characterizing breast tumor in contrast-enhanced MR images. STEP captures not only the dynamic enhancement and architectural features of tumor, but also the spatial variations of pixel-wise temporal enhancement of tumor. Although the latter has been widely used by radiologist during diagnosis, it is rarely considered as important features for computer-aided tumor diagnosis. Notice that, by regarding serial contrast-enhanced images as a single spatial-temporal image, STEP can capture all types of the features within a single framework. In particular, a Fourier transformation is used to extract various temporal enhancement features, followed by moment invariants to capture spatial patterns of each temporal enhancement feature. Experimental results show the better performance of our designed STEP features than many other features available in the literature. The area under ROC curve can reach 0.96 with our STEP features in tumor diagnosis.
KW - Breast tumor diagnosis
KW - Feature extraction
KW - Magnetic resonance imaging
UR - http://www.scopus.com/inward/record.url?scp=36349015390&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=36349015390&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2007.356903
DO - 10.1109/ISBI.2007.356903
M3 - Conference contribution
AN - SCOPUS:36349015390
SN - 1424406722
SN - 9781424406722
T3 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
SP - 520
EP - 523
BT - 2007 4th IEEE International Symposium on Biomedical Imaging
Y2 - 12 April 2007 through 15 April 2007
ER -