Minimally Invasive Spine surgery (MISS) was developed to treat disorders of the spine with less disruption to the muscles. Surgeons use CT images to monitor the volume of muscles after operation in order to evaluate t...Minimally Invasive Spine surgery (MISS) was developed to treat disorders of the spine with less disruption to the muscles. Surgeons use CT images to monitor the volume of muscles after operation in order to evaluate the progress of patient recovery. The first step in the task is to segment the muscle regions from other tissues/organs in CT images. However, manual segmentation of muscle regions is not only inaccurate, but also time consuming. In this work, Gray Space Map (GSM) is used in fuzzy c-means clustering algorithm to segment muscle regions in CT images. GSM com- bines both spatial and intensity information of pixels. Experiments show that the proposed GSM- based fuzzy c-means clustering muscle CT image segmentation yields very good results.展开更多
To guarantee the accuracy and real-time of the 3D reconstruction method for outdoor scene,an algorithm based on region segmentation and matching was proposed.Firstly,on the basis of morphological gradient information,...To guarantee the accuracy and real-time of the 3D reconstruction method for outdoor scene,an algorithm based on region segmentation and matching was proposed.Firstly,on the basis of morphological gradient information,obtained by comparing color weight gradient images and proposing a multi-threshold segmentation,scene contour features were extracted by a watershed algorithm and a fuzzy c-means clustering algorithm.Secondly,to reduce the search area,increase the correct matching ratio and accelerate the matching speed,the region constraint was established according to a region＇s local position,area and gray characteristics,the edge pixel constraint was established according to the epipolar constraint and the continuity constraint.Finally,by using the stereo matching edge pixel pairs,their 3D coordinates were estimated according to the binocular stereo vision imaging model.Experimental results show that the proposed method can yield a high stereo matching ratio and reconstruct a 3D scene quickly and efficiently.展开更多
文摘Minimally Invasive Spine surgery (MISS) was developed to treat disorders of the spine with less disruption to the muscles. Surgeons use CT images to monitor the volume of muscles after operation in order to evaluate the progress of patient recovery. The first step in the task is to segment the muscle regions from other tissues/organs in CT images. However, manual segmentation of muscle regions is not only inaccurate, but also time consuming. In this work, Gray Space Map (GSM) is used in fuzzy c-means clustering algorithm to segment muscle regions in CT images. GSM com- bines both spatial and intensity information of pixels. Experiments show that the proposed GSM- based fuzzy c-means clustering muscle CT image segmentation yields very good results.
基金Supported by the Ministerial Level Advanced Research Foundation(40401060305)
文摘To guarantee the accuracy and real-time of the 3D reconstruction method for outdoor scene,an algorithm based on region segmentation and matching was proposed.Firstly,on the basis of morphological gradient information,obtained by comparing color weight gradient images and proposing a multi-threshold segmentation,scene contour features were extracted by a watershed algorithm and a fuzzy c-means clustering algorithm.Secondly,to reduce the search area,increase the correct matching ratio and accelerate the matching speed,the region constraint was established according to a region＇s local position,area and gray characteristics,the edge pixel constraint was established according to the epipolar constraint and the continuity constraint.Finally,by using the stereo matching edge pixel pairs,their 3D coordinates were estimated according to the binocular stereo vision imaging model.Experimental results show that the proposed method can yield a high stereo matching ratio and reconstruct a 3D scene quickly and efficiently.
