Titlebook: Biomedical Image Registration; Third International Josien P. W. Pluim,Boštjan Likar,Frans A. Gerritse Conference proceedings 2006 Springer

interminable

书目名称Biomedical Image Registration影响因子(影响力)




书目名称Biomedical Image Registration影响因子(影响力)学科排名




书目名称Biomedical Image Registration网络公开度




书目名称Biomedical Image Registration网络公开度学科排名




书目名称Biomedical Image Registration被引频次




书目名称Biomedical Image Registration被引频次学科排名




书目名称Biomedical Image Registration年度引用




书目名称Biomedical Image Registration年度引用学科排名




书目名称Biomedical Image Registration读者反馈




书目名称Biomedical Image Registration读者反馈学科排名

PALSY

Indigence

Automatic Inter-subject Registration of Whole Body Images,sor-based morphometry. A number of methods have been proposed to tackle this problem but few of them have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which

窗帘等

Local Intensity Mapping for Hierarchical Non-rigid Registration of Multi-modal Images Using the Croach in image registration. For multi-modal images mutual information is the usual choice for the measure of patch similarity. As already recognized in the literature, the statistical consistency of mutual information is drastically reduced when it is estimated for regions covering only a limited num

Bother

Arboreal

Removal of Interpolation Induced Artifacts in Similarity Surfaces,the other is found by maximizing a similarity measure. Similarity surfaces are subject to scalloping artifacts due to interpolation that give local maxima, and, in some cases, erroneous global maxima. We propose a new linear filter that is applied to input images and which removes scalloping artifac

极少

HALO

座右铭

Canonical Correlation Analysis of Sub-cortical Brain Structures Using Non-rigid Registration,y statistically relative to each other. Canonical correlation analysis is a multivariate statistical technique which extracts and quantifies correlated behaviour between two sets of vector variables. Firstly, we perform non-rigid image registration of 93 sets of 3D MR images to build sets of surface

armistice

A Novel 3D/2D Correspondence Building Method for Anatomy-Based Registration,igid, has been proven to improve the accuracy and precision of various image-guided therapies. One of the key steps for a successful anatomy-based registration is to establish 3D/2D correspondence between the 3D model and the 2D images. This paper presents a novel 3D/2D correspondence building metho