Datasets

subject: Biomedical Engineering type: dataset

Total is 41 Results
Automatic 4D flow MRI Segmentation Using the Standardized Difference of Means Velocity

10.4231/F75X-1N34

Bruce Craig ORCID logo , Jiacheng Zhang ORCID logo , Michael Markl , Neal Patel , Pavlos Vlachos ORCID logo , Sameer Ansari , Sean Michael Rothenberger ORCID logo , Susanne Schnell , Vitaliy Rayz

02/02/2023

We provide 4D flow MRI velocity measurements in two in vitro flow phantoms of a cerebral aneurysm. One phantom is unscaled (1-to-1), and the other is scaled by a factor of two in all dimensions (2-to-1).

angiography Biomedical Engineering hemodynamics Magnetic Resonance Velocimetry Matlab Phase Contrast Magnetic Resonance Imaging

mHealth hyperspectral learning for hemodynamics

10.4231/VAFP-DW68

Young L Kim ORCID logo

03/27/2023

A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hyperspectral learning is capable of recovering full spectroscopic resolution

Biomedical Engineering hemodynamics Matlab mHealth spectral learning

Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal

10.4231/R7WQ01R7

Haiguang Wen , Zhongming Liu ORCID logo

09/30/2015

Matlab toolbox for separating the fractal (scale-free) component and oscillatory component in the power spectrum from the mixed time series

Bioinformatics Biomedical Engineering fractal scale-free

A Non-parametric Bayesian Model for Joint Cell Clustering and Cluster Matching: Identification of Anomalous Sample Phenotypes with Random Effects.

10.4231/R7KK98PG

Bartlomiej P. Rajwa , Ferit Akova , Halid Ziya Yerebakan , Murat Dundar

09/03/2014

The manuscript presents a non-parametric Bayesian algorithm called ASPIRE (Anomalous Sample Phenotype Identification with Random Effects) able to identify phenotypic differences across batches of cytometry samples in the presence of random effects

AML Bayesian Biomedical Engineering BMC Bioinformatics Computer Science cytometry Dirichlet process Gaussian mixture model Interdisciplinary Research Life Sciences random effects

Next Generation Calmodulin Affinity Purification Data

10.4231/R7Q81B9G

Julia Fraseur , Tamara L Kinzer-Ursem ORCID logo

06/01/2018

Coomassie-stained gels used in semi-quantitative analysis of purified calcineurin from calmodulin Sepharose resins.

Biomedical Engineering Calcineurin Calmodulin Protein

MicroCT based FE model of bone core with tissue heterogeneity and anisotropy

10.4231/R7CC0XX4

Joseph Wallace , Matthew R Allen , Max A Hammond , Thomas Siegmund ORCID logo

06/26/2018

This publication contains a finite element model for the analysis of bone core under consideration of bone tissue heterogeneity and tissue anisotropy.

Biomedical Engineering Bone Finite Element Analysis Mechanical Engineering

A Multi-state Model of the CaMKII Holoenzyme using MCell 3.3

10.4231/MV0Z-8Z57

Matthew C Pharris , Tamara L Kinzer-Ursem ORCID logo

07/29/2019

This model uses a specialized rule-based syntax in MCell 3.3 to model the twelve-subunit CaMKII holoenzyme without inducing combinatorial explosion. The model allows us to explore the regulation of CaMKII activation and autophosphorylation.

Biomedical Engineering Calcium Calmodulin Computational Modeling Kinase Neuroscience Protein Signaling Rule-Based Modeling Synaptic Plasticity

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