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- Creator:
- Dariya, Malyarenko, Tariq, Humera, Kushwaha, Aman, Mourad, Rami, Heist, Kevin, Chenevert, Thomas L, Ross, Brian D, Chen, Heang-Ping, and Hadjiiski, Lubomir
- Description:
- The 3D GRE MRI data for murine model of myelofbifrosis with expert segmentations of mouse tibia was used to train Attention UNET model to automate bone marrow segmentation for measurements of imaging biomarkers. This dataset consists of three archives: (1) containing the source MRI images in Meta-image-header (MHD) format with resulting segmentation labels by two experts and four UNET models with different training scenarios; (2) corresponding training models; and (3) deep-learning (DL)-based segmentation tools for application to future murine tibia MRI data. and The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. The image archive is structured with a directory tree that contains \"mouseID"\"scan-date"\"segmentaion-scenario"\. The "training model" archive containes DL-model labeled by the data subset, and "deployment" archive containes the DL-segmentation software.
- Keyword:
- deep-learning segmentation, preclinical MRI, murine tibia, and mouse model of myelofibrosis
- Citation to related publication:
- Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 2023 Mar 7;9(2):589-602. doi: 10.3390/tomography9020048. PMID: 36961007; PMCID: PMC10037585. and https://github.com/dumichgh/MFJK1_Segmentation_MHDs
- Discipline:
- Health Sciences
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- Creator:
- Hong, Yi, Fry, Lauren M., Orendorf, Sophie, Ward, Jamie L., Mroczka, Bryan, Wright, David, and Gronewold, Andrew
- Description:
- Accurate estimation of hydro-meteorological variables is essential for adaptive water management in the North American Laurentian Great Lakes. However, only a limited number of monthly datasets are available nowadays that encompass all components of net basin supply (NBS), such as over-lake precipitation (P), evaporation (E), and total runoff (R). To address this gap, we developed a daily hydro-meteorological dataset covering an extended period from 1979 to 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and R was calculated from National Water Model (NWM) simulations. Ensemble mean values of the difference between P and E (P – E) and NBS were obtained by analyzing daily P, E, and R. Monthly averaged values derived from our new daily dataset were validated against existing monthly datasets. This daily hydro-meteorological dataset has the potential to serve as a validation resource for current data and analysis of individual NBS components. Additionally, it could offer a comprehensive depiction of weather and hydrological processes in the Great Lakes region, including the ability to record extreme events, facilitate enhanced seasonal analysis, and support hydrologic model development and calibration. The source code and data representation/analysis figures are also made available in the data repository.
- Keyword:
- Great Lakes, Hydrometeorological, National Water Model, Daily, Overlake precipitation, Overlake evaporation, Total runoff, Net Basin Supply, and Water Balance
- Discipline:
- Science and Engineering
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- Creator:
- Liemohn, Michael W
- Description:
- Earth’s upper atmosphere above 500 km altitude constantly loses charged particles to outer space in a process called ionospheric outflow. This outflow is important for the dynamics of the near-Earth space environment (“space weather”) yet is poorly understood on a global scale. A mission is needed to observe the global patterns of ionospheric outflow and its relation to space weather driving conditions. The science objectives of such a mission could include not only the reconstruction of global outflow patterns but also the relation of these patterns to geomagnetic activity and the spatial and temporal nature of outflow composition. A study is presented to show that four well-placed spacecraft would be sufficient for reasonable outflow reconstructions.
- Keyword:
- ionosphere, magnetosphere, satellite mission concept, and space weather
- Citation to related publication:
- Liemohn, M. W., Jörg-Micha Jahn, Raluca Ilie, Natalia Y. Ganushkina, Daniel T. Welling, Heather Elliott, Meghan Burleigh, Kaitlin Doublestein, Stephanie Colon-Rodriguez, Pauline Dredger, & Philip Valek (2024). Reconstruction analysis of global ionospheric outflow patterns. Journal of Geophysical Research Space Physics, 129, e2023JA032238. https://doi/org/10.1029/2024JA032238
- Discipline:
- Science
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