caa a22 4500 463178459 CHVBK 20180406164832.0 cr unu---uuuuu 170326e20070901xx s 000 0 eng 10.1007/s10278-006-1041-6 doi (NATIONALLICENCE)springer-10.1007/s10278-006-1041-6 Level Set Contouring for Breast Tumor in Sonography [Elektronische Daten] [Yu-Len Huang, Yu-Ru Jiang, Dar-Ren Chen, Woo Moon] The echogenicity, echotexture, shape, and contour of a lesion are revealed to be effective sonographic features for physicians to identify a tumor as either benign or malignant. Automatic contouring for breast tumors in sonography may assist physicians without relevant experience, in making correct diagnoses. This study develops an efficient method for automatically detecting contours of breast tumors in sonography. First, a sophisticated preprocessing filter reduces the noise, but preserves the shape and contrast of the breast tumor. An adaptive initial contouring method is then performed to obtain an approximate circular contour of the tumor. Finally, the deformation-based level set segmentation automatically extracts the precise contours of breast tumors from ultrasound (US) images. The proposed contouring method evaluates US images from 118 patients with breast tumors. The contouring results, obtained with computer simulation, reveal that the proposed method always identifies similar contours to those obtained with manual sketching. The proposed method provides robust and fast automatic contouring for breast US images. The potential role of this approach might save much of the time required to sketch a precise contour with very high stability. SCAR (Society for Computer Applications in Radiology), 2007 Ultrasonography nationallicence breast neoplasm nationallicence computer-aided diagnosis (CAD) nationallicence image segmentation nationallicence radiographic image interpretation nationallicence level set method nationallicence Huang Yu-Len Department of Computer Science and Information Engineering, Tunghai University, 407, Taichung, Taiwan, Republic of China aut Jiang Yu-Ru Department of Computer Science and Information Engineering, Tunghai University, 407, Taichung, Taiwan, Republic of China aut Chen Dar-Ren Department of Diagnostic Radiology, Seoul National University Hospital, Seoul, South Korea aut Moon Woo Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan, Republic of China aut Journal of Digital Imaging Springer-Verlag; http://www.springer-ny.com 20/3(2007-09-01), 238-247 0897-1889 20:3<238 2007 20 10278 https://doi.org/10.1007/s10278-006-1041-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10278-006-1041-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Huang Yu-Len Department of Computer Science and Information Engineering, Tunghai University, 407, Taichung, Taiwan, Republic of China aut NATIONALLICENCE 700 1- Jiang Yu-Ru Department of Computer Science and Information Engineering, Tunghai University, 407, Taichung, Taiwan, Republic of China aut NATIONALLICENCE 700 1- Chen Dar-Ren Department of Diagnostic Radiology, Seoul National University Hospital, Seoul, South Korea aut NATIONALLICENCE 700 1- Moon Woo Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan, Republic of China aut NATIONALLICENCE 773 0- Journal of Digital Imaging Springer-Verlag; http://www.springer-ny.com 20/3(2007-09-01), 238-247 0897-1889 20:3<238 2007 20 10278 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer