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- Creators: Kodibagkar, Vikram
- Creators: Arizona Board of Regents
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In January 2014, Mary Gatter and colleagues published “Relationship between Ultrasound Viewing and Proceeding to Abortion” in Obstetrics and Gynecology hereafter “Ultrasound Viewing.” As of 2021, ten states require women to undergo an ultrasound before they may consent to having an abortion. Self-described pro-life organizations assert that viewing an image of the fetus will dissuade women from having an abortion. The authors reviewed women’s medical records from over fifteen thousand visits to one abortion provider in 2011.The authors determined viewing an ultrasound image did not change the minds of women who were already highly certain that abortion was the right decision, challenging the idea that mandatory ultrasound viewing has any effect on women’s decision to have an abortion.
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In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
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The methods developed in this work improve the spatial coverage of whole-brain DSC-MRI by combining a highly efficient 3D spiral k-space trajectory with Generalized Autocalibrating Partial Parallel Acquisition (GRAPPA) parallel imaging without increasing temporal resolution. The proposed method is capable of acquiring 30 slices with a temporal resolution of under 1 second, covering the entire cerebrum with isotropic spatial resolution of 3 mm. Additionally, the acquisition method allows for correction of T1-enhancing leakage effects by virtue of collecting two echoes, which confound DSC perfusion measurements. The proposed DSC-perfusion method results in high quality perfusion parameter maps across a larger volume than is currently available with current clinical standards, improving diagnostic utility of perfusion MRI methods, which ultimately improves patient care.