TY - GEN
T1 - Facilitating manual segmentation of 3d datasets using contour and intensity guided interpolation
AU - Ravikumar, Sadhana
AU - Wisse, Laura
AU - Gao, Yang
AU - Gerig, Guido
AU - Yushkevich, Paul
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Manual segmentation of anatomical structures in 3D imaging datasets is a highly time-consuming process. This process can be sped up using interslice interpolation techniques, which require only a small subset of slices to be manually segmented. In this paper, we propose a two-step interpolation approach that utilizes a 'binary weighted averaging' algorithm to interpolate contour information, and the random forest framework to perform intensity-based label classification. We present the results of experiments performed in the context of hippocampal segmentations in ex vivo MRI scans. Compared to the random walker algorithm and morphology-based interpolation, the proposed method produces more accurate segmentations and smoother 3D reconstructions.
AB - Manual segmentation of anatomical structures in 3D imaging datasets is a highly time-consuming process. This process can be sped up using interslice interpolation techniques, which require only a small subset of slices to be manually segmented. In this paper, we propose a two-step interpolation approach that utilizes a 'binary weighted averaging' algorithm to interpolate contour information, and the random forest framework to perform intensity-based label classification. We present the results of experiments performed in the context of hippocampal segmentations in ex vivo MRI scans. Compared to the random walker algorithm and morphology-based interpolation, the proposed method produces more accurate segmentations and smoother 3D reconstructions.
KW - 3D segmentation
KW - Contour interpolation
KW - Random forest
UR - http://www.scopus.com/inward/record.url?scp=85073889655&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073889655&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2019.8759500
DO - 10.1109/ISBI.2019.8759500
M3 - Conference contribution
AN - SCOPUS:85073889655
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 714
EP - 718
BT - ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Y2 - 8 April 2019 through 11 April 2019
ER -