Magnetic resonance imaging Category

Short Term Reproducibility of a High Contrast 3-D Isotropic Optic Nerve Imaging Sequence in Healthy Controls

Feb. 1, 2016—Robert L. Harrigan, Alex K. Smith, Louise A. Mawn, Seth A. Smith, Bennett A. Landman. “Short Term Reproducibility of a High Contrast 3-D Isotropic Optic Nerve Imaging Sequence in Healthy Controls.” In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2016. Oral presentation. Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862660/?report=classic Abstract The optic nerve (ON) plays a...

Figure 2
Illustration of minimally rater performance relative to an experienced rater for T1 data (A) and T2 data (B). The top row shows 200 slices which have been expertly labeled sorted by the median overlap with minimally trained raters. The center row shows the number of times each slice has been labeled. The final row illustrates an arbitrary example from the lowest, median, and highest accuracy slices.

Collaborative Labeling of Malignant Glioma with WebMILL: A First Look

Feb. 1, 2012—E. Singh, Z. Xu, A. Asman, L. Chambless, R. Thompson and B. Landman. “Collaborative Labeling of Malignant Glioma with WebMILL: A First Look.” In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2012 † Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Collaborative+Labeling+of+Malignant+Glioma+with+WebMILL%3A+A+First+Look Abstract Malignant gliomas are the most common form of primary neoplasm in the central nervous...

Figure 3
Kurtosis of weighted residuals. The Kurtosis maps of the residuals from the weighted data are shown in the first column. The middle and the right column display one voxel residuals across the first 100 scans inside the cerebrospinal fluid region and the white matter region respectively.

A Comparison of Distributional Considerations with Statistical Analysis of Resting State fMRI at 3T and 7T

Feb. 1, 2012—Xue Yang, Martha J. Holmes, Allen T. Newton, Victoria L. Morgan, Bennett A. Landman. “A Comparison of Distributional Considerations with Statistical Analysis of Resting State fMRI at 3T and 7T.” In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2012 (Oral Presentation) NIHMS341654† Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=A+Comparison+of+Distributional+Considerations+with+Statistical+Analysis+of+Resting+State+fMRI+at+3T+and+7T Abstract Ultra-high field 7T magnetic resonance...

Figure 2
Results from the controlled rater observation simulation. The target intensity image and the corresponding true labels can be seen (A) and (B), respectively. The set of input observations used in this experiment can be seen in (C). The results of the four algorithms, Majority Vote, STAPLE, Binary-COLLATE and Multi-COLLATE can be seen in (D)–(G). Note that the 3 consensus-level implementation of Multi-COLLATE is the only algorithm that gets the correct answer. The 3 energy in each of the consensus levels can be seen in (H)–(J). Note that by distributing the non-consensus voxels into two separate levels, (H) and (I), the estimation process converges to the correct answer.

Generalized Statistical Label Fusion using Multiple Consensus Levels

Feb. 1, 2012—Z. Xu, A. Asman and B. Landman. “Generalized Statistical Label Fusion using Multiple Consensus Levels.” In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2012 (Oral Presentation) PMC3438516† Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=%E2%80%9CGeneralized+Statistical+Label+Fusion+using+Multiple+Consensus+Levels. Abstract Segmentation plays a critical role in exposing connections between biological structure and function. The process of label fusion collects and...

$Example potential application of HUBRIS for the reconstruction of improved diffusion tensor imaging (DTI) fractional anisotropy (FA) maps using a multi-shot acquisition. The presented color maps from single-shot (a) and multi-shot (b) echo-planar imaging (EPI) data show multi-shot EPI exhibits reduced blurring and geometric distortions. The generation of the improved images requires a custom reconstruction algorithm that can be accessed by HUBRIS.$

“Integrating Medical Imaging Analyses through a High-throughput Bundled Resource Imaging System”

Aug. 11, 2011—Kelsie Covington, E. Brian Welch, Bennett A. Landman. “Integrating Medical Imaging Analyses through a High-throughput Bundled Resource Imaging System”, In Proceedings of the SPIE Medical Imaging Conference. Lake Buena Vista, Florida, February 2011 (Oral Presentation) PMC3154704† Full text Abstract Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities...

FA estimates with acquired data. Systematic bias is seen between DTEMRL and LLMMSE when simultaneously using all 15 datasets (A,B). Mean differences (bias) between methods are preserved when single datasets are analyzed (C,D). Variability of DTEMRL is lower throughout the brain (E,F).

Diffusion Tensor Estimation by Maximizing Rician Likelihood

Oct. 1, 2007—B. A. Landman, P-L. Bazin, and J. L. Prince. “Diffusion Tensor Estimation by Maximizing Rician Likelihood”, In Proceedings of the 2007 International Conference on Computer Vision Workshop on Mathematical Methods in Biomedical Image Analysis, Rio de Janeiro, Brazil, October 2007. (Oral Presentation) Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3488430/ Abstract Diffusion tensor imaging (DTI) is widely used to characterize...