Title :
Automatic femur segmentation and condyle line detection in 3D MR scans for alignment of high resolution MR
Author :
Jolly, M.-P. ; Alvino, C. ; Odry, B. ; Deng, X. ; Zheng, J. ; Harder, M. ; Guehring, J.
Author_Institution :
Imaging & Visualization Dept., Siemens Corp. Res., Princeton, NJ, USA
Abstract :
This paper describes an automatic algorithm to extract the knee frame of reference from 3D MR isotropic scans. The method ultimately seeks to determine two lines that are tangent to the bottom of the condyles in an axial and a coronal plane. It consists of three major parts, initial detection of the knee joint using Hidden Markov Models, femur segmentation using Random Walker segmentation, and finally condyle detection. We demonstrate on 30 datasets that our algorithm is very robust and performs at the same level as a human reader.
Keywords :
biomedical MRI; bone; hidden Markov models; image reconstruction; image resolution; image segmentation; medical image processing; 3-D MR isotropic scan; automatic femur segmentation; condyle line detection; hidden Markov model; high resolution MR alignment; knee Scan Planning; knee joint; random walker segmentation; Coils; Hidden Markov models; High-resolution imaging; Image segmentation; Knee; Ligaments; Magnetic resonance imaging; Medical services; Planning; Visualization; Hidden Markov Models; Knee Scan Planning; Magnetic Resonance Imaging; Random Walker Segmentation;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2010.5490142