We have to use MATLAB code to answer and plot these answers butI am not sure how to even get values out of the .mat file that datais located in.
| BME 443/543 Assignment: PET imaging and analysis Due: November 19, 2019, 5pm Complete the deliverables listed below and upload to Canvas. Please upload each file separately (don’t compress or make them a .zip file) • Matlab m-file with code to answer the following questions • A report (saved as a PDF or PPT) of answers and figures to support your answer • Make sure each plot/figure has a title, labeled axes, and is displayed in the correct aspect **Prior to beginning this homework, I would highly suggest working through the example PET imaging data and visualizing 4D data matlab code (examplePETcode.m). It uses data loaded into the HW4_data.mat) For problem (1) use control_dX and treated_dx. Control_dx and treated_dx are both structures with the following pieces of information; control_dx. SUV: SUV image (128 x 128 x 159 slices); control_dx.roi_tumor: ROI over tumor control_dx.roi_muscle: ROI over muscle; d0,d1,d2,03,04, d7 correspond to the number of days following treatment. Day O is a pre-treatment image (baseline) (1) We have two mice that were imaged with 18F-MISO PET(These are located in the HW4_data.mat). 18F-MISO is a PET tracer (i.e. contrast agent that accumulates (and is retained) in hypoxic cells. Mice with HER2+ breast cancer received injections of either saline (control group) or trastuzumab (treated group). Trastuzumab primarily inhibits cell proliferation, however, it also has been known to suppress angiogenesis (blood vessel formation). Tumors tend to overexpress angiogenic factors resulting in abnormal vasculature (poor perfusion and delivery, leakv). Suppressing angiogenic factors results in the “normalization” of tumor vasculature and potentially improving tissue perfusion. a. How is tumor hypoxia related to tumor vasculature? b. (2 Plots) Calculate the SUV in muscle at each time point for the control and treated mouse i. (1st plot) Plot the mean and 95% confidence interval. ii. (2nd plot) Plot the mean and 95% confidence interval normalize the means to day O’s value. c. (2 Plots) Calculate the SUV in tumor at each time point for the control and treated mouse i. (1st plot) Plot the mean and 95% confidence interval. ii. (2nd plot) Plot the mean and 95% confidence interval. Normalize the means to day O’s value. Show transcribed image text | BME 443/543 Assignment: PET imaging and analysis Due: November 19, 2019, 5pm Complete the deliverables listed below and upload to Canvas. Please upload each file separately (don’t compress or make them a .zip file) • Matlab m-file with code to answer the following questions • A report (saved as a PDF or PPT) of answers and figures to support your answer • Make sure each plot/figure has a title, labeled axes, and is displayed in the correct aspect **Prior to beginning this homework, I would highly suggest working through the example PET imaging data and visualizing 4D data matlab code (examplePETcode.m). It uses data loaded into the HW4_data.mat) For problem (1) use control_dX and treated_dx. Control_dx and treated_dx are both structures with the following pieces of information; control_dx. SUV: SUV image (128 x 128 x 159 slices); control_dx.roi_tumor: ROI over tumor control_dx.roi_muscle: ROI over muscle; d0,d1,d2,03,04, d7 correspond to the number of days following treatment. Day O is a pre-treatment image (baseline) (1) We have two mice that were imaged with 18F-MISO PET(These are located in the HW4_data.mat). 18F-MISO is a PET tracer (i.e. contrast agent that accumulates (and is retained) in hypoxic cells. Mice with HER2+ breast cancer received injections of either saline (control group) or trastuzumab (treated group). Trastuzumab primarily inhibits cell proliferation, however, it also has been known to suppress angiogenesis (blood vessel formation). Tumors tend to overexpress angiogenic factors resulting in abnormal vasculature (poor perfusion and delivery, leakv). Suppressing angiogenic factors results in the “normalization” of tumor vasculature and potentially improving tissue perfusion. a. How is tumor hypoxia related to tumor vasculature? b. (2 Plots) Calculate the SUV in muscle at each time point for the control and treated mouse i. (1st plot) Plot the mean and 95% confidence interval. ii. (2nd plot) Plot the mean and 95% confidence interval normalize the means to day O’s value. c. (2 Plots) Calculate the SUV in tumor at each time point for the control and treated mouse i. (1st plot) Plot the mean and 95% confidence interval. ii. (2nd plot) Plot the mean and 95% confidence interval. Normalize the means to day O’s value.
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Answer to We have to use MATLAB code to answer and plot these answers but I am not sure how to even get values out of the .mat fil…