Survey: NiChart User

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Dear participant,

We are still in the early stages of designing NiChart, and your feedback will help us improving it.

Your feedback will be used to inform our design process and ensure that we are creating a project that meets the needs of our users.

The survey should take no longer than 5 minutes to complete. All responses will be anonymous.

Please provide any feedback that you might have and wasn't addressed by the questions at the bottom of this form.

Thank you for your participation!

What important are these aspects to you?

Please check your response. *

Not important

Somewhat Important

Very important

Image processing methods

DL-based image segmentation methods

The diversity and breadth of the reference dataset

Data harmonization to the large reference dataset

Machine learning models for deriving biomarkers

Visualization tools that display image features and biomarkers in comparison to reference data distributions

Cloud application for applying pipeline steps without installation or compute resources

Not important

Somewhat Important

Very important

Image processing methods

DL-based image segmentation methods

The diversity and breadth of the reference dataset

Data harmonization to the large reference dataset

Machine learning models for deriving biomarkers

Visualization tools that display image features and biomarkers in comparison to reference data distributions

Cloud application for applying pipeline steps without installation or compute resources

"NiChart is a framework that integrates image processing, data harmonization and machine learning for deriving disease and aging biomarkers from multi-modal MRI images"

Is this definition clear?

Yes

Please select all options that apply to you

What features or functionality would you like to see in the final product?"
*

Integration of novel image processing methods for deriving additional imaging features

Addition of machine learning models that were trained on other diseases and conditions (e.g. diabetes, autism, multiple sclerosis, etc.))

Addition of novel unsupervised or semi-supervised ML methods in addition to more standard supervised predictive models

Improved visualization tools

Image processing methods that run significantly faster

Providing users the ability to add their own methods and models

Improving the cloud application

Addition of other image modalities (ASL, PET)

Providing models that can be directly applied to single scans without harmonization

Other:

Required

To what extent do you agree or disagree with each of the following statements below?

A more integrated framework could potentially be a valuable asset to my research.

Strongly Disagree

Strongly Agree

I plan to use pre-trained machine learning models to calculate biomarkers from my dataset.
*

Strongly Disagree

Strongly Agree

Was it easy to use the cloud application? (https://neuroimagingchart.com/portal/)

N/A (I did not use or test it)

Yes

Did NiChart work smoothly, providing desirable and meaningful results to your usage?

N/A (I did not use or test it)

Yes

How likely are you to recommend the cloud application to a colleague?
*

Not Likely

Extremely Likely

Please provide us with comments on what we could improve on. (ex. Add specific plotting features, etc.)

Additional comments or suggestions:

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