Titlebook: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013; 16th International C Kensaku Mori,Ichiro Sakuma,Nassir Navab Con

尽责

A Symmetric 4D Registration Algorithm for Respiratory Motion Modelingand temporal non-smoothness, and inverse inconsistency. We test our algorithm for respiratory motion estimation on public benchmarks and on clinic lung CT data. The experimental results demonstrate the efficacy of our algorithm.

枯萎将要

Respiratory Motion Correction in Dynamic-MRI: Application to Small Bowel Motility Quantification duroid errors in further analysis of motility due to the effects of breathing. The proposed method is assessed using regions of interest (ROIs) contoured in dynamic MRI of six healthy volunteers. The use of RDDR prior to motility quantification results in reduced errors on motility scores in ROIs, with respect to breath-holds.

Allergic

Conference proceedings 2013d Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 86 papers included in the second volume have been organized

Exposition

CEDE

未开化

Canopy

Large Deformation Diffeomorphic Registration of Diffusion-Weighted Images with Explicit Orientation ows . diffusion model to be fitted after registration for subsequent multifaceted analysis. This is achieved by directly aligning the diffusion-weighted images using a large deformation diffeomorphic registration framework formulated from an optimal control perspective. Our algorithm seeks the optim

招募

Atlas Construction for Dynamic (4D) PET Using Diffeomorphic Transformationstomograph (HRRT), the highest resolution human brain PET scanner available in the world. By extending the recent diffeomorphic log-demons (DLD) method and applying it to multiple dynamic [.C]raclopride scans from the HRRT, an important step towards construction of a PET atlas of unprecedented qualit

LAY

Harpoon

A Histology-Based Model of Quantitative T1 Contrast for In-vivo Cortical Parcellation of High-Resoluguration) does not exist today. In this paper we present a generative model which can predict, on the basis of known cytoarchitecture, myeloarchitecture in different primary and non-primary cortical areas, resulting in simulated in-vivo quantitative T1 maps. The predicted patterns can be used in bra