Which data structure for multidimensional MRI data (multiple methods, slices, segments) in R?












0















I am still a beginner in R and have been using Excel to organize my data and it is very messy, so I want to put everything in some data structure in R to later visualize it.



My data consists of values obtained from an algorithm that analyzes each pixel of MRI images of an organ. The images are obtained using two different methods (method A and B), and the organ is imaged in 8 slices, covering the entire organ. Each image of the organ is segmented into 6 anatomical segments, and our MATLAB code takes the average and SD of the pixels in each segment.



At the end of the analysis, I have 4 tables. Two for averages (one for each method) and two for SD values (one for each method). The columns of the tables represent segments (segments 1-6) and the rows are the slices (slices 1-8). This is for one patient, and we are scanning several patients.



I want to organize the data such that it is easy to create visualizations such that I can compare different methods for all patients, or look at the values for the different slices, or simply look at specific segments.



If I use one dataframe, should each observation be a slice? Or a single value from a single slice and segment? Should I use multiple dataframes? I am a little lost on how to best organize this, as I've had no previous experience with datasets.



Thank you for your help, and if more clarification is needed, please let me know.










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  • Please make your question more clear. stackoverflow.com/help/how-to-ask

    – Florian
    Nov 19 '18 at 20:29
















0















I am still a beginner in R and have been using Excel to organize my data and it is very messy, so I want to put everything in some data structure in R to later visualize it.



My data consists of values obtained from an algorithm that analyzes each pixel of MRI images of an organ. The images are obtained using two different methods (method A and B), and the organ is imaged in 8 slices, covering the entire organ. Each image of the organ is segmented into 6 anatomical segments, and our MATLAB code takes the average and SD of the pixels in each segment.



At the end of the analysis, I have 4 tables. Two for averages (one for each method) and two for SD values (one for each method). The columns of the tables represent segments (segments 1-6) and the rows are the slices (slices 1-8). This is for one patient, and we are scanning several patients.



I want to organize the data such that it is easy to create visualizations such that I can compare different methods for all patients, or look at the values for the different slices, or simply look at specific segments.



If I use one dataframe, should each observation be a slice? Or a single value from a single slice and segment? Should I use multiple dataframes? I am a little lost on how to best organize this, as I've had no previous experience with datasets.



Thank you for your help, and if more clarification is needed, please let me know.










share|improve this question

























  • Please make your question more clear. stackoverflow.com/help/how-to-ask

    – Florian
    Nov 19 '18 at 20:29














0












0








0








I am still a beginner in R and have been using Excel to organize my data and it is very messy, so I want to put everything in some data structure in R to later visualize it.



My data consists of values obtained from an algorithm that analyzes each pixel of MRI images of an organ. The images are obtained using two different methods (method A and B), and the organ is imaged in 8 slices, covering the entire organ. Each image of the organ is segmented into 6 anatomical segments, and our MATLAB code takes the average and SD of the pixels in each segment.



At the end of the analysis, I have 4 tables. Two for averages (one for each method) and two for SD values (one for each method). The columns of the tables represent segments (segments 1-6) and the rows are the slices (slices 1-8). This is for one patient, and we are scanning several patients.



I want to organize the data such that it is easy to create visualizations such that I can compare different methods for all patients, or look at the values for the different slices, or simply look at specific segments.



If I use one dataframe, should each observation be a slice? Or a single value from a single slice and segment? Should I use multiple dataframes? I am a little lost on how to best organize this, as I've had no previous experience with datasets.



Thank you for your help, and if more clarification is needed, please let me know.










share|improve this question
















I am still a beginner in R and have been using Excel to organize my data and it is very messy, so I want to put everything in some data structure in R to later visualize it.



My data consists of values obtained from an algorithm that analyzes each pixel of MRI images of an organ. The images are obtained using two different methods (method A and B), and the organ is imaged in 8 slices, covering the entire organ. Each image of the organ is segmented into 6 anatomical segments, and our MATLAB code takes the average and SD of the pixels in each segment.



At the end of the analysis, I have 4 tables. Two for averages (one for each method) and two for SD values (one for each method). The columns of the tables represent segments (segments 1-6) and the rows are the slices (slices 1-8). This is for one patient, and we are scanning several patients.



I want to organize the data such that it is easy to create visualizations such that I can compare different methods for all patients, or look at the values for the different slices, or simply look at specific segments.



If I use one dataframe, should each observation be a slice? Or a single value from a single slice and segment? Should I use multiple dataframes? I am a little lost on how to best organize this, as I've had no previous experience with datasets.



Thank you for your help, and if more clarification is needed, please let me know.







r dataframe






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edited Nov 19 '18 at 20:36







senidog

















asked Nov 19 '18 at 20:11









senidogsenidog

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11













  • Please make your question more clear. stackoverflow.com/help/how-to-ask

    – Florian
    Nov 19 '18 at 20:29



















  • Please make your question more clear. stackoverflow.com/help/how-to-ask

    – Florian
    Nov 19 '18 at 20:29

















Please make your question more clear. stackoverflow.com/help/how-to-ask

– Florian
Nov 19 '18 at 20:29





Please make your question more clear. stackoverflow.com/help/how-to-ask

– Florian
Nov 19 '18 at 20:29












1 Answer
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You can flatten out the rows. So basically, you would have 48 (i.e. 6 x 8) columns and as many rows as the number of patients.






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  • This is rather a comment than an answer.

    – Florian
    Nov 19 '18 at 20:30











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1 Answer
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active

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1 Answer
1






active

oldest

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active

oldest

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active

oldest

votes









0














You can flatten out the rows. So basically, you would have 48 (i.e. 6 x 8) columns and as many rows as the number of patients.






share|improve this answer
























  • This is rather a comment than an answer.

    – Florian
    Nov 19 '18 at 20:30
















0














You can flatten out the rows. So basically, you would have 48 (i.e. 6 x 8) columns and as many rows as the number of patients.






share|improve this answer
























  • This is rather a comment than an answer.

    – Florian
    Nov 19 '18 at 20:30














0












0








0







You can flatten out the rows. So basically, you would have 48 (i.e. 6 x 8) columns and as many rows as the number of patients.






share|improve this answer













You can flatten out the rows. So basically, you would have 48 (i.e. 6 x 8) columns and as many rows as the number of patients.







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 19 '18 at 20:24









pooja ppooja p

1297




1297













  • This is rather a comment than an answer.

    – Florian
    Nov 19 '18 at 20:30



















  • This is rather a comment than an answer.

    – Florian
    Nov 19 '18 at 20:30

















This is rather a comment than an answer.

– Florian
Nov 19 '18 at 20:30





This is rather a comment than an answer.

– Florian
Nov 19 '18 at 20:30




















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