利用层间相关性的岩心CT图像半自动分割方法

目的 由于岩心CT图像分辨率不高,目标边界较为模糊,无法完全自动化地对岩心CT图像的目标分割和提取。为保证效果,在分割过程中往往需要进行人为干预。但作为3维重建的岩心CT图像,图像数据规模较大,达到成百上千帧。如果对每一帧都进行人为干预,工作量将会很大。针对这种情况提出一种在保证分割效果的前提下只需进行少量人为干预的高效实用的分割方法。方法 先对CT图像中的某一帧设定分割阈值,利用CT图像层间相关性对相邻帧自动计算合适的分割阈值,从而分割出整个CT图中的目标。并根据需要,选定其中分割效果较好的一帧,其他帧根据此帧进行自动区域生长修复,从而更加完善分割效果。还可以手工修复其中一帧中的目标,其余帧的所有相关目标将会自动进行识别和修复。结果 通过对多组不同数据规模和分辨率的岩心CT图像进行实验测试,使用本文方法均可达到期望的分割效果,并且分割速度较大津分割法提高近1倍,与固定阈值分割方法速度相当。结论 岩心CT图像分割方法充分利用图像层间相关性,可快速有效地批量提取具有连续性的序列图像中的目标。

Semi-segmentation of rock CT images using the correlation of adjacent frames

Objective Automatically segmenting rock CT images is difficult because of the low resolution and fuzzy edges of rock CT images. To achieve desired results, human intervention is necessary in the segmentation process. However, the CT image data for 3D model reconstruction is considerably large. In this case, the workload becomes too heavy to achieve a successful intervention for each frame. In this work, we propose an efficient and practical method that can ensure desired segmentation results with little human intervention. Method An original threshold is first set. This original threshold comes from one of the CT images used in the study. Then, the threshold for segmenting adjacent frames is calculated automatically using the correlation of the adjacent frames. In this way, all the segmentation objects from the rock CT images are successfully obtained. If necessary, all the CT images are repaired with an automatic region growing method according to the frame with perfect segmentation to improve segmentation. Manual repair is found to be useful when automatic repair is unsuccessful. After the manual repair of some of the objects in one frame, the correlative targets of the other frames are segmented automatically with the proposed method. Improved results are obtained. Result By testing a series of rock CT images with various scales and resolutions, we find that the method proposed in this work can achieve the desired segmentation at speeds equal to that of the segmentation method based on a fixed threshold and double that of the OSTU method. Conclusion The proposed segmentation method for rock CT images maximizes the correlation of adjacent frames and can quickly and efficiently extract objects from continuous images in sequence.