semantic segmentation for magnetic resonance imaging
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Updated
Sep 21, 2021 - Python
semantic segmentation for magnetic resonance imaging
meta-analysis of new and published human WAT single cell data
A simple toolbox of ImageJ plugins for quantifying adipocyte morphology and function in tissues and in vitro.
Algorithm created with Python to semi-automatically segment various depots of fat based on a Dixon sequence abdominal MRI scan. Anatomical landmarks of the MRI scan must be manually identified.
Python pipelines for analysis of adipocyte scRNA-seq data
Code for the IJMS paper (Co-Expression Network Analysis of AMPK and Autophagy Gene Products during Adipocyte Differentiation)
This program will take in MRI images in the NIFTI format and display them on the screen. The user will draw a closed contour around specified areas of fat at multiple axial slices. These results are saved in a file to be validated with the VisceralFatSegmentation program. This program is created using Qt and C++.
Data and analysis results for the MoTrPAC PASS1B rat white adipose tissue manuscript
Helper Functions for the MotrpacRatTraining6moWATData R Package
INVESTIGATING THE ASSOCIATION BETWEEN POLYGENIC RISK SCORE OF ADIPOSE TISSUE FUNCTION AND CARDIOVASCULAR DISEASE
Python & R scripts collection for AdipoAtlas project
20.440 Group Project-Intercellular Communication in vivo
Tabula Muris Senis Transcriptomic Secretome Database Generation + White Adipose Depot Analysis
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