scispace - formally typeset
R

Richard Castillo

Researcher at Emory University

Publications -  89
Citations -  3562

Richard Castillo is an academic researcher from Emory University. The author has contributed to research in topics: Image registration & Medicine. The author has an hindex of 26, co-authored 76 publications receiving 3081 citations. Previous affiliations of Richard Castillo include Hospital Universitario La Paz & University of Texas MD Anderson Cancer Center.

Papers
More filters
Journal ArticleDOI

A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets.

TL;DR: It is demonstrated that landmark pairs can be used to assess DIR spatial accuracy within a narrow uncertainty range and based on fewer than the required validation landmarks results in misrepresentation of the relative spatial accuracy.
Journal Article

Attenuation Correction of PET Images with Respiration-Averaged CT Images in PET/CT

TL;DR: The use of respiration-averaged CT (ACT) to match the temporal resolution of CT and PET and the improvement of tumor quantification in PET images of the thorax with ACT was evaluated and breathing artifacts were significantly reduced by ACT.
Journal ArticleDOI

Implementation and evaluation of various demons deformable image registration algorithms on a GPU

TL;DR: In this article, a gray-scale-based deformable image registration (DIR) algorithm called demons and five of its variants were implemented on GPUs using the compute unified device architecture (CUDA) programming environment.
Journal ArticleDOI

Four-dimensional deformable image registration using trajectory modeling.

TL;DR: The 4DLTM method captures the long-range motion between 4DCT extremes with high spatial accuracy and is compared with an alternative registration approach in which component phase to phase (CPP) DIR is utilized to determine the full displacement between maximum inhale and exhale images.
Journal ArticleDOI

Implementation and evaluation of various demons deformable image registration algorithms on GPU

TL;DR: It is interesting to find out that the original passive force demons algorithms outperform subsequently proposed variants based on the combination of accuracy, efficiency and ease of implementation.