Welcome!

This is the online ePortfolio of Jun Hu, Justin Shek (0842536), and Arthur Wong (0957192), students in the Medical Radiation Sciences [Radiography] program with McMaster University and Mohawk College.

Radiographic imaging is a fundamental component of diagnosis in the clinical setting. However, there are various potential sources of error that can produce images that are unusable for diagnosis. The aim of quality control in the radiographic imaging setting is to minimize errors made because of human or apparatus error.

The content of this ePortfolio pertains to the labs, modules, assignments, and assessments of our quality control course, MEDRADSC 3H03: Quality Control in Radiography. By discussing the expectations, goals, and achievements of the aforementioned material, we hope to show how our understanding and appreciation of quality control practices in a radiographic setting will progress.

We have chosen to create this ePortfolio through an online blog format over other formats for three reasons:

1. Various media formats (text, audio, video, images, etc.) are supported
2. Online hosting makes updates and posts possible from virtually anywhere
3. Updates can be added at the poster's leisure and are not restricted to any one user's computer

Furthermore, by posting directly online it is our hope that information and knowledge in this ePortfolio can be more rapidly shared with the world than through conventional means.

Thursday, March 8, 2012

DR Flatfield QC


               Although pixels look small, they make big impacts when it comes to diagnostic imaging. A pixel’s duty is to receive the beam electrons and then later transfer the data and form an image or a radiograph.  If there are a lot of non-functioning pixels in a detector, it would greatly decrease the quality of the image.   Each pixel contains a unique data that other pixels cannot be replaced and that is why pixel’s condition is so important.  It is important to check every 3 to 6 months to see if all the pixels are still functioning normally. Otherwise, dead pixels would show up as artifacts or white dots and other technologists might think it is an actual artifact and might lead to an unnecessary repeat.
             Since pixels play such a big role, I think it is important to maintain it quality.  A Quality Assurance Procedures, or formerly known as QAP is the only way to test if there are any dead pixels in a detector. As mentioned above, too many dead pixels will decrease the quality of the image because the dead pixels will appear white and shown as artifacts.  Having such artifacts will affect the result of diagnosis because the artifacts might be on the exact same spot of pathology.  Each manufacturer has a different acceptance range of bad pixels. According to GE, the manufacturer of our machine, the pass or fail depends on the number of dead pixels. Here is our test result.


                  As seen above, there was only one dead pixel and we passed the image quality test. We should keep track of each month’s QAP to see if there are any more dead pixels, because eventually, the dead pixels would accumulate and fail the quality assurance test.  If we do not perform any QAP, the dead pixels will gives us troubles during our labs because of the numbers of the dead pixels. This is another reason why quality control should be carried, so that the equipments are kept at high quality and utilize itself.



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