Titlebook: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006; 9th International Co Rasmus Larsen,Mads Nielsen,Jon Sporring Conf

LH941

书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006影响因子(影响力)




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006影响因子(影响力)学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006网络公开度




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006网络公开度学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006被引频次




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006被引频次学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006年度引用




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006年度引用学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006读者反馈




书目名称Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006读者反馈学科排名

工作

呼吸

bronchiole

Repetitions

一美元

受人支配

GPU Based Real-Time Instrument Tracking with Three Dimensional Ultrasoundng at the 26 volumes per second rate of the ultrasound machine. A water tank experiment found instrument tip position errors of less than 0.2 mm, and an . study tracked an instrument inside a beating porcine heart. The tracking results showed good correspondence to the actual movements of the instrument.

Counteract

Shape-Driven 3D Segmentation Using Spherical Waveletsmization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

Barter

Segmenting Lung Fields in Serial Chest Radiographs Using Both Population and Patient-Specific Shape number of serial images is small; gradually, patient-specific shape statistics takes more rules after a sufficient number of segmentation results on the same patient have been obtained. The proposed deformable model can adapt to the shape variability of different patients, and obtain more robust and accurate segmentation results.

GLADE

Comparing the Similarity of Statistical Shape Models Using the Bhattacharya Metrichod of comparing statistical shape models by evaluating the Bhattacharya overlap between their implied shape distributions. We apply the technique to investigate the similarity of three models of the same 3D dataset constructed using different methods.