FACILITATING MANUAL SEGMENTATION OF 3D DATASETS USING CONTOUR ANDINTENSITY GUIDED INTERPOLATION
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. 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.
Ravikumar, S., Wisse, L., Gao, Y., Gerig, G., & Yushkevich, P. (2019, April). Facilitating Manual Segmentation of 3D Datasets Using Contour And Intensity Guided Interpolation. In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) (pp. 714-718). IEEE.