TY - GEN
T1 - Numerical experiments for segmenting medical images using level sets
AU - Araújo, A.
AU - Comissiong, D. M.G.
AU - Stadler, G.
PY - 2008
Y1 - 2008
N2 - Image segmentation is the process by which objects are separated from background information. Structural segmentation from 2D and 3D images is an important step in the analysis of medical image data. In this work, we utilize level set algorithms and active contours without edges to segment two and three-dimensional image data. Besides synthetical data, we also use magnetic resonance images of the human brain provided by the Institute of Biomedical Research in Light and Images of the University of Coimbra (IBILI).
AB - Image segmentation is the process by which objects are separated from background information. Structural segmentation from 2D and 3D images is an important step in the analysis of medical image data. In this work, we utilize level set algorithms and active contours without edges to segment two and three-dimensional image data. Besides synthetical data, we also use magnetic resonance images of the human brain provided by the Institute of Biomedical Research in Light and Images of the University of Coimbra (IBILI).
UR - http://www.scopus.com/inward/record.url?scp=60749090585&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=60749090585&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:60749090585
SN - 9780415457774
T3 - Proceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
SP - 91
EP - 96
BT - Proceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
T2 - VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
Y2 - 17 October 2007 through 19 October 2007
ER -