Featured Articles Archives - IEEE Transactions on Medical Imaging (TMI)

February 4, 2019

Learning a Probabilistic Model for Diffeomorphic Registration

Author(s): Julian Krebs, Herve Delingette, Boris Mailhé, Nicholas Ayache, Tommaso Mansi

Learning a Probabilistic Model for Diffeomorphic Registration https://www.embs.org/tmi/wp-content/uploads/sites/21/2019/02/slide34.jpg 1200 709 IEEE Transactions on Medical Imaging (TMI) IEEE Transactions on Medical Imaging (TMI) //www.embs.org/tmi/wp-content/uploads/sites/21/2022/06/ieee-tmi-logo2x.png February 4, 2019 March 4, 2022

We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations…

January 24, 2019

Efficient Multiple Organ Localization in CT Image Using 3D Region Proposal Network

Efficient Multiple Organ Localization in CT Image Using 3D Region Proposal Network IEEE Transactions on Medical Imaging (TMI) IEEE Transactions on Medical Imaging (TMI) //www.embs.org/tmi/wp-content/uploads/sites/21/2022/06/ieee-tmi-logo2x.png January 24, 2019 March 4, 2022

Organ localization is an essential preprocessing step for many medical image analysis tasks, such as image registration, organ segmentation, and lesion detection. In this paper, we propose an efficient method…

December 12, 2018

DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography

Author(s): Ehsan Samei, Brian Harrawood, Shobhit Sharma, Anuj Kapadia, William P. Segars

DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography https://www.embs.org/tmi/wp-content/uploads/sites/21/2018/12/slide32.jpg 1200 500 IEEE Transactions on Medical Imaging (TMI) IEEE Transactions on Medical Imaging (TMI) //www.embs.org/tmi/wp-content/uploads/sites/21/2022/06/ieee-tmi-logo2x.png December 12, 2018 March 4, 2022

The purpose of this study was to develop a CT simulation platform that is: 1) compatible with voxel-based computational phantoms; 2) capable of modeling the geometry and physics of commercial…

November 1, 2018

Learning-Based Quality Control for Cardiac MR Images

Author(s): Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Antonio de Marvao, Declan P. O`Regan, Stuart Cook, Ben Glocker, Paul M. Matthews, Daniel Rueckert

Learning-Based Quality Control for Cardiac MR Images https://www.embs.org/tmi/wp-content/uploads/sites/21/2018/11/slide31.jpg 1200 500 IEEE Transactions on Medical Imaging (TMI) IEEE Transactions on Medical Imaging (TMI) //www.embs.org/tmi/wp-content/uploads/sites/21/2022/06/ieee-tmi-logo2x.png November 1, 2018 March 4, 2022

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the…

April 30, 2018

Connectivity in fMRI: Blind Spots and Breakthroughs

Author(s): Victor Solo, Jean-Baptiste Poline, Martin A. Lindquist, Sean L. Simpson, F. DuBois Bowman, Moo K. Chung, Ben Cassidy

Connectivity in fMRI: Blind Spots and Breakthroughs https://www.embs.org/tmi/wp-content/uploads/sites/21/2018/04/slide28.jpg 1200 500 IEEE Transactions on Medical Imaging (TMI) IEEE Transactions on Medical Imaging (TMI) //www.embs.org/tmi/wp-content/uploads/sites/21/2022/06/ieee-tmi-logo2x.png April 30, 2018 March 4, 2022

In recent years, driven by scientific and clinical concerns, there has been an increased interest in the analysis of functional brain networks. The goal of these analyses is to better…