Results 31 to 40 of about 399,723 (262)

Learning Rigid Image Registration - Utilizing Convolutional Neural Networks for Medical Image Registration [PDF]

, 2018
Many traditional computer vision tasks, such as segmentation, have seen large step-changes in accuracy and/or speed with the application of Convolutional Neural Networks (CNNs).
Goatman, K.A., Siebert, J.P., Sloan, J.M.   +2 more
core   +1 more source

DTR-GAN: An Unsupervised Bidirectional Translation Generative Adversarial Network for MRI-CT Registration

Applied Sciences, 2023
Medical image registration is a fundamental and indispensable element in medical image analysis, which can establish spatial consistency among corresponding anatomical structures across various medical images.
Aolin Yang, Tiejun Yang, Xiang Zhao, Xin Zhang, Yanghui Yan, Chunxia Jiao   +5 more
doaj   +1 more source

Groupwise Multimodal Image Registration using Joint Total Variation [PDF]

, 2020
In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.), to highlight different structures or pathologies.
A Collignon, A Myronenko, A Roche, AV Cideciyan, C Studholme, C Wachinger, C Wu, DL Hill, DN Greve, E Haber, F Maes, FP Oliveira, G Sapiro, J Ashburner, J Huang, J Orchard, JBA Maintz, JP Lewis, JP Pluim, JV Hajnal, M Brudfors, M Polfliet, P Blomgren, P Gerlot-Chiron, P Snape, P Viola, RP Woods, RP Woods, WH Press, WM Wells III, X Bresson, ZS Saad, Ž Spiclin   +32 more
core   +2 more sources

macJNet: weakly-supervised multimodal image deformable registration using joint learning framework and multi-sampling cascaded MIND

BioMedical Engineering OnLine, 2023
Deformable multimodal image registration plays a key role in medical image analysis. It remains a challenge to find accurate dense correspondences between multimodal images due to the significant intensity distortion and the large deformation. macJNet is
Zhiyong Zhou, Ben Hong, Xusheng Qian, Jisu Hu, Minglei Shen, Jiansong Ji, Yakang Dai   +6 more
doaj   +1 more source

Attention Guided Policy Optimization for 3D Medical Image Registration

IEEE Access, 2023
Learning-based image registration approaches typically learn to map from input images to a transformation matrix. Regarding the current deep-learning-based image rigid registration approaches learn a transformation matrix in a one-shot way.
Jing Hu, Zhikun Shuai, Xin Wang, Shu Hu, Shanhui Sun, Siwei Lyu, Xi Wu   +6 more
doaj   +1 more source

Homologous point transformer for multi-modality prostate image registration [PDF]

PeerJ Computer Science, 2022
Registration is the process of transforming images so they are aligned in the same coordinate space. In the medical field, image registration is often used to align multi-modal or multi-parametric images of the same organ.
Alexander Ruchti, Alexander Neuwirth, Allison K. Lowman, Savannah R. Duenweg, Peter S. LaViolette, John D. Bukowy   +5 more
doaj   +2 more sources

Fast Fluid Registration of medical images [PDF]

, 1996
This paper offers a new fast algorithm for non-rigid Viscous Fluid Registration of medical images that is at least an order of magnitude faster than the previous method by Christensen et al. [4]. The core algorithm in the fluid registration method is based on a linear elastic deformation of the velocity field of the fluid.
Bro-Nielsen, Morten, Gramkow, Claus
openaire   +2 more sources

Registration and analysis for images couple : Application to mammograms

ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2014
In this thesis, the problem addressed is the development of a computer-aided diagnosis system (CAD) based on conjoint analysis of several images, and therefore on the comparison of these medical images.
Arnaud Boucher
doaj   +1 more source

Locally Orderless Registration [PDF]

, 2012
Image registration is an important tool for medical image analysis and is used to bring images into the same reference frame by warping the coordinate field of one image, such that some similarity measure is minimized.
Darkner, Sune, Sporring, Jon
core   +2 more sources

Dimensionality reduction of medical image descriptors for multimodal image registration

Current Directions in Biomedical Engineering, 2015
Defining similarity forms a challenging and relevant research topic in multimodal image registration. The frequently used mutual information disregards contextual information, which is shared across modalities.
Degen Johanna, Modersitzki Jan, Heinrich Mattias P.   +2 more
doaj   +1 more source