DocumentCode :
1937073
Title :
Computerized Segmentation and Classification of Breast Lesions Using Perfusion Volume Fractions in Dynamic Contrast-enhanced MRI
Author :
Lee, Sang Ho ; Kim, Jong Hyo ; Park, Jeong Seon ; Chang, Jung Min ; Park, Sang Joon ; Jung, Yun Sub ; Moon, Woo Kyung
Author_Institution :
Coll. of Med., Interdiscipl. Programs in Radiat. Appl. Life Sci. major, Seoul Nat. Univ., Seoul
Volume :
2
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
58
Lastpage :
62
Abstract :
This study is designed to segment suspicious regions using automatic computerized procedures and to classify kinetic patterns using commercially available three-time-points (3TP) method of computer- aided diagnosis. A novel evaluation method using perfusion volume fractions is introduced for examining meaningful kinetic features in differentiation of benign and malignant breast lesions. Dynamic contrast- enhanced MRI was applied to 24 lesions (12 malignant, 12 benign). Thresholding for suspicious regions, region growing segmentation, hole-filling and 3D morphological erosion and dilation were performed for extracting final lesion volume. The lesion sphericity and center distance of mass to surface area ratio (CDMSAR) were considered in the process of automatic segmentation. The kinetic patterns for each lesion were classified into six classes by the 3TP method. Perfusion volume fraction for each class was calculated in three partitions of whole, rim and core volumes of a lesion. Receiver operating characteristic curve (ROC) analysis was performed using the perfusion volume fractions. When using perfusion volume fractions divided into rim and core lesion volume, the classes having more improved accuracy appeared than using perfusion volume fractions within whole lesion volume. This result indicates that lesion classification using local perfusion volume fractions is helpful in selecting meaningful kinetic patterns for differentiation of benign and malignant lesions.
Keywords :
biological organs; biomedical MRI; gynaecology; image segmentation; medical image processing; 3D morphological erosion; breast lesions; computer-aided diagnosis; computerized segmentation; dilation; dynamic contrast-enhanced MRI; hole-filling; kinetic patterns; perfusion volume fractions; sphericity; three-time-points method; Biomedical computing; Biomedical engineering; Biomedical informatics; Breast; Cancer; Kinetic theory; Lesions; Magnetic resonance imaging; Medical diagnostic imaging; Neoplasms; Breast MRI; kinetics; three-time-points method; tumor segmentation; volume measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-0-7695-3118-2
Type :
conf
DOI :
10.1109/BMEI.2008.215
Filename :
4549135
Link To Document :
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