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 **Mentors:** Puneet Sharma (puneet.sharma -at- emory.edu) and Tony Pan (tony.pan -at- emory.edu)
 
-**Overview:** In this project, we intend to assess whether or not a series of MR images encompass the anatomy if interest, specifically for brain regions. The contributor will develop a methodology to auto-detect and measure the extent of anatomical coverage on brain MR images, and determine whether it is compliant with expected "bounding boxes" set forth by pre-defined protocol constraints.  For example, a protocol may require specific anatomical coverage (e.g. top of the head to ~C2/3 vertebral bodies, with left ear-to-right ear extent), which must be met by acquired MR image data . This module will be part of a larger pipeline to assess overall quality and compliance on MRI modalities.
+**Overview:** In this project, we intend to assess whether or not a series of MR images encompass the anatomy of interest, specifically for brain regions. The contributor will develop a methodology to auto-detect and measure the extent of anatomical coverage on brain MR images, and determine whether it is compliant with expected "bounding boxes" set forth by pre-defined protocol constraints.  For example, a protocol may require specific anatomical coverage (e.g. top of the head to ~C2/3 vertebral bodies, with left ear-to-right ear extent), which must be met by acquired MR image data . This module will be part of a larger pipeline to assess overall quality and compliance on MRI modalities.
 
 **Current Status:** This is a new module to run on DICOM images, specifically brain MRI images in DICOM format. This module will execute on DICOM images acquired in real-time or on-demand by Niffler. For testing purposes during the application period and early stages of development, brain MRI images obtained from public data sources such as [the Cancer Imaging Archive (TCIA)](https://www.cancerimagingarchive.net/) can be used.