Morphology-based Interslice Interpolation using Local Intensity Information for Segmentation
The interpolation of contours between slices in the absence of the original intensity image has been a challenging task and investigated for many years. In some applications of medical imaging, however, objects of interest are segmented manually on selected slices and the intensity image is available. The latter can be used to improve the quality of interpolated segmentations. In this paper, we present a two-step approach to accurate interslice interpolation of manual segmentations using information from both object shape and image intensity. Morphology based shape interpolation followed by the application of intensity-based neighborhood voting to adjust boundary voxels were used to integrate the two information sources. We compared our method to three existing interpolation methods for magnetic resonance images of mouse and human brain. The proposed method outperformed the three methods, having lower average error rates.
Interslice interpolation shape-based interpolation mathematical morphology conditional dilation local intensity information.
Xiaochun Liao David Reutens Zhengyi Yang
School of Information Engineering Southwest University of Science and Technology Mianyang, China Centre for Advanced Imaging The University of Queensland Brisbane, Australia
国际会议
上海
英文
384-389
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）