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- Creator:
- Herzog, Joshua M, Verkade, Angela, and Sick, Volker
- Description:
- Data deposited here includes 60 image sets (30 individual participants, and 2 eyes per individual) consisting of raw fluorescence images, diffuse reflection images using ambient lighting, images used for correction, and calibration, and metadata. Images are split into two wavelength bands as described in the methodology. Raw images are stored in Hierarchical Data Format 5 (HDF5) file nodes (one file per eye) and each image node contains a tag for frame rate, exposure duration, and timestamp (stored in ImageData.zip). Summary statistics including demographic data, participant-reported diseases (e.g., diabetes, keratoconus), and pupil size are also stored in a text-based comma-separated table and as an Excel spreadsheet. Finally, 2-channel pseudocolor images and ratiometric grayscale images combining the two fully-processed image bands are stored as portable network graphics (PNG) files (stored in PseudocolorImages.zip).
- Keyword:
- Fluorescence, Imaging, Ocular lens, Corneal disease, Cataract, and Diabetes
- Citation to related publication:
- Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Corneal shadowgraphy: a simple, low-cost, rapid, and quantitative tool with potential clinical utility." Manuscript in review. 2024. and Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Quantitative and rapid in vivo imaging of human lenticular fluorescence." Manuscript in review. 2024.
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- Figueroa, Carlos A., Computational Vascular Biomechanics Lab, University of Michigan, and et al.
- Description:
- This collection concerns the CRIMSON (CardiovasculaR Integrated Modelling and SimulatiON) software environment. CRIMSON provides a powerful, customizable and user-friendly system for performing three-dimensional and reduced-order computational haemodynamics studies via a pipeline which involves: 1) segmenting vascular structures from medical images; 2) constructing analytic arterial and venous geometric models; 3) performing finite element mesh generation; 4) designing, and 5) applying boundary conditions; 6) running incompressible Navier-Stokes simulations of blood flow with fluid-structure interaction capabilities; and 7) post-processing and visualizing the results, including velocity, pressure and wall shear stress fields. , The minimum specifications to run CRIMSON are: Any AMD64 CPU (note: Intel Core i series are AMD64), Windows (only tested on Windows 10 but might work on Windows 7), 8 GB of RAM , If you are running non-trivial models you will want to have: Quad core CPU or higher, Solid state drive for storing data, Windows, 16 GB of RAM, Dedicated discrete GPU for rendering models. , and Software in this collection is a snapshot; please visit https://github.com/carthurs/CRIMSONGUI & www.crimson.software for more general information and the most up to date version of the software.
- Keyword:
- Blood Flow Simulation, Patient-specific, Open-source Software, Image-based simulation, Cardiovascular Medical Image, Segmentation, and Finite Element Simulation
- Citation to related publication:
- CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, et al. bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960
- Discipline:
- Health Sciences and Engineering
4Works -
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Raghani, Ravi M, Urie, Russell R, and Shea, Lonnie D
- Description:
- The IN were sampled during and after ICB and sequenced to identify gene expression signatures that correlated with sensitivity or resistance. We also analyzed gene expression at the IN prior to ICB treatment to identify markers predicting therapeutic response. Longitudinally interrogating an IN, to monitor changes associated with ICB response, presents a new opportunity to personalize care and investigate mechanisms underlying treatment resistance.
- Keyword:
- Immunotherapy resistance, Biomaterials, Metastasis, Checkpoint blockade, and Therapy monitoring
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Szuromi, Matthew P. and Stacey, William C.
- Description:
- The data and scripts are meant to show how burster dynamics determine response to a single biphasic stimulus. The files include data which show trends in the propensity of termination for different burster types and the MATLAB scripts used to generate this data. The MATLAB scripts also allow the user to generate their own data sets for alternative bursting paths and stimulus parameter combinations. Furthermore, they allow the user to visually examine the effects of single stimuli in the voltage timeseries and in state space. How the user can access these features of the script is described in the file "ReadMe.pdf."
- Keyword:
- Epilepsy, Stimulation, Modelling, Dynamics, Seizure, and Dynamotype
- Citation to related publication:
- (PROVISIONAL) Optimization of Ictal Aborting Stimulation Using the Dynamotype Taxonomy
- Discipline:
- Health Sciences, Engineering, and Science
-
- Creator:
- Whitaker, Steven T., Nataraj, Gopal, Nielsen, Jon-Fredrik, and Fessler, Jeffrey A.
- Description:
- File: P,jf06Sep2019,mese.7 The multi-echo spin echo (MESE) data was acquired using a 3D acquisition with an initial 90 degree excitation pulse followed by 32 refocusing (180 degree) pulses, resulting in 32 echoes with echo spacing of 10 ms. The repetition time of the sequence was 1200 ms. Each refocusing pulse was flanked by crusher gradients to impart 14 cycles of phase across the imaging volume. The initial excitation pulse had time-bandwidth product of 6, duration of 3 ms, and slab thickness of 0.9 cm, and each refocusing pulse had time-bandwidth product of 2, duration of 2 ms, and slab thickness of 2.1 cm. The scan took 36 min 11 s and covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: P,jf06Sep2019,b1.7 The Bloch-Siegert (BS) scans were acquired using a 3D acquisition. The excitation pulse of these scans had time-bandwidth product of 8 and duration of 1 ms. The pair of scans used +/-4 kHz off-resonant Fermi pulses between excitation and readout. The BS scans took 2 min 40 s in total and covered a FOV of 22 x 22 x 0.99 cm^3 with matrix size 200 x 50 x 9., File: P,jf06Sep2019,mwf.7 The small-tip fast recovery (STFR) scans were acquired using a 3D acquisition. The first two and last two scans were pairs of spoiled gradient-recalled echo (SPGR) scans with echo time difference of 2.3 ms. (In the related paper, only the first set was used, i.e., only 11 of the 13 scans were used.) The remaining scans used scan parameters that were optimized to minimize the Cramer-Rao Lower Bound (CRLB) of estimates of myelin water fraction (MWF). The RF pulses had time-bandwidth product of 8 and duration of 1 ms. Each pair of SPGR scans took 58 s and the nine STFR scans took 3 min 36 s for a total scan time of 5 min 32 s (4 min 34 s if one pair of SPGR scans is ignored). The scans covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: meseslice5.mat Contains the 32 echoes of the MESE image data for the middle slice of the imaging volume. Saved using Mathworks MATLAB R2019a., File: b1slice5.mat Contains the transmit field inhomogeneity map for the middle slice of the imaging volume., File: recon.jld Key "img" contains the 11 STFR images for the middle slice of the imaging volume. Key "b0map" contains a field map estimated from the two SPGR scans. Key "mask" contains a mask of the voxels for which to estimate MWF. Key "T1img" contains a T1-weighted image for anatomical reference., File: headmask.mat Contains a mask for visualizing just the brain (ignores the skull) for the middle slice of the imaging volume., File: rois.mat Contains masks for various regions of interest (ROIs), used for computing statistics. Keys "mtopleft", "mtopright", "mbottomleft", and "mbottomright" refer to the corresponding locations on the anatomical reference image (see related paper). Key "mic" refers to the internal capsules, and key "mgm" refers to a gray matter ROI., The raw data files (P-files) can be read into the Julia programming language using the Julia version of the Michigan Image Reconstruction Toolbox ( https://github.com/JeffFessler/MIRT.jl) or into MATLAB using TOPPE ( https://github.com/toppeMRI/toppe). The reconstructed slices used in the related paper are provided for convenience, and are stored in .mat files that can be loaded into Julia (using the package MAT.jl) or MATLAB, and a .jld file that can be loaded into Julia (using the package JLD.jl). The Julia code for processing the data to create MWF maps is hosted publicly on GitHub at https://github.com/StevenWhitaker/STFR-MWF., and Files: toppe-master.zip and MIRT.jl-master.zip are archived versions of the TOPPE and Michigan Image Reconstruction Toolbox code sets from GitHub as of 2/28/2020.
- Keyword:
- myelin, machine learning, kernel learning, magnetic resonance imaging, and scan design
- Citation to related publication:
- Whitaker, S. T., Nataraj, G., Nielsen, J.-F., & Fessler, J. A. (2020). Myelin water fraction estimation using small-tip fast recovery MRI. Magnetic Resonance in Medicine, 84(4), 1977–1990. https://doi.org/10.1002/mrm.28259
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- Crisp, Dakota N., Cheung, Warwick, Gliske, Stephen V., Lai, Alan, Freestone, Dean R., Grayden, David B., Cook, Mark J., and Stacey, William C.
- Description:
- The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
- Keyword:
- evoked response, stimulation, bifurcation, epilepsy, seizure, divergence, and dynamics
- Citation to related publication:
- Crisp, D. N., Cheung, W., Gliske, S. V., Lai, A., Freestone, D. R., Grayden, D. B., Cook, M. J., & Stacey, W. C. (2020). Quantifying epileptogenesis in rats with spontaneous and responsive brain state dynamics. Brain Communications, 2(1). https://doi.org/10.1093/braincomms/fcaa048
- Discipline:
- Science, Engineering, and Health Sciences
-
- Creator:
- Figueroa, C. Alberto
- Description:
- This information provides the data and commands to manually setup the computational simulations used in the PLOS ONE paper 'Patient-specific modeling of right coronary circulation vulnerability post-liver transplant in Alagille’s syndrome' using CRIMSON (CARDIOVASCULAR INTEGRATED MODELLING & SIMULATION) a prototype simulation environment developed under the support of the European Research Council (( http://www.crimson.software/)., Note that a Windows version of the CRIMSON flowsolver is provided as part of the CRIMSON Windows installer, but you will need a very powerful Windows computer to run these simulations, as the models used in the present work are extremely computationally-demanding. It is recommended that you use a Linux version of the CRIMSON flowsolver on a high-performance computer., Option 1 (ready-to-use files to immediately start the simulation): 1. Please unzip the Ready-to-use files. 2. Copy the folders of each of the three conditions to the high performance computer. 3. In addition to different codes used, each folder provides the boundary conditions applied in the simulations described in the manuscript (e.g. LPN parameters). To run the 3D simulations for each condition simply launch the it using the CRIMSON flowsolver. In addition, the solver.inp file can be modified to run a 0D "real-time simulation" (please open solver.inp with a text editor and modify line 4 "Simulate in Purely Zero Dimensions:" to "True")., Option 2 (using the MITK files): 1. Please download and install Crimson software ( http://www.crimson.software/). 2. Please unzip the MITK files and the Ready-to-use files. 3. From amongst the provided MITK files, load the MITK file of interest to CRIMSON (using the MITK files, additional changes can be made to the computational model in case the user wants to explore different settings/boundary conditions e.g. change the vascular wall properties, introducing a change in the geometry to create a virtual stenosis). 3. Navigate to the tree in the "Data Manager" panel and select the "Pulmonaries", "CRIMSON SOLVER" and then "Solver study 3D" items, in the described order. 4. In the right hand panel select the "CRIMSON Solver setup" tab and scroll down the right hand bar until to find the "Setup Solver" box; click to output the simulation files (faceInfo.dat, geombc.dat.1, multidomain.dat, netlist_surface.dat,numstart.dat, presolver folder, solver.inp, restart.0.1). 5. Copy and replace the geombc.dat.1 and restart.0.1 generated by CRIMSON for each individual condition to the respective unziped folder in the Ready-to-use file (discard the remaining files that were output by CRIMSON). Note that if you have not changed anything about the model (e.g. vascular wall properties), then doing this will produce restart.0.1 and geombc.dat.1 files which are identical to the ready-to-use versions. 6. Finally copy each Condition folder to the high performance computer and simply launch the simulation using the CRIMSON flowsolver., and For technical queries please contact crimson-users@googlegroups.com. --October 2018.
- Citation to related publication:
- Silva Vieira M, Arthurs CJ, Hussain T, Razavi R, Figueroa CA (2018) Patient-specific modeling of right coronary circulation vulnerability post-liver transplant in Alagille’s syndrome. PLOS ONE 13(11): e0205829. https://doi.org/10.1371/journal.pone.0205829
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Crisp, Dakota N., Parent, Rachel, Nakatani, Mitsuyoshi, Murphy, Geoffrey G. , and Stacey, William C.
- Description:
- This data and scripts are meant to test and show that seizure onset dynamics can be modulated using anti-epileptic drugs. A zip file is included that contains all waveform data, MATLAB processing scripts, and metadata. The MATLAB scripts allow for visual review validation and objective feature analysis. The file includes various README files explaining the scripts and their relationships in greater detail.
- Keyword:
- Bifurcation, Epilepsy, Seizure, and Electrophysiology
- Discipline:
- Health Sciences, Engineering, and Science
-
- Creator:
- Attari, Ali
- Description:
- Please refer to the "README.txt" for more details., MATLAB R2018a (Mathworks, Natick, MA, USA) was used to process this data., and Excel (Microsoft Office) was used to store survey data on the comfort of both systems and also to provide absolute and relative intraobserver variablities for the DM device.
- Keyword:
- Digital Manometry
- Citation to related publication:
- Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system Attari A, Chey WD, Baker JR, Ashton-Miller JA (2020) Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system. PLOS ONE 15(9): e0228761. https://doi.org/10.1371/journal.pone.0228761
- Discipline:
- Engineering, Science, and Health Sciences
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