Frequency Encoding Gradient | MRI Signal Localisation | MRI Physics Course #8

High yield radiology physics past paper questions with video answers
Perfect for testing yourself prior to your radiology physics exam 👇
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Now that we have selected a slice along the longitudinal axis let's review how we can manipulate the pulse sequence to isolate signal in the x axis of the slice. This process is known as the frequency encoding gradient (FEG).
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Not sure if the question banks are for you?
If you're here, you're likely studying for a radiology physics exam. I've spent the last few months collating past papers from multiple different countries selecting the most commonly asked questions. You'll be surprised how often questions repeat themselves!
The types of questions asked in FRCR, RANZCR AIT, ARRT, FC Rad Diag (SA), ABR qualifying Core Physics and MICR part 1 are surprisingly similar and the key concepts remain the same throughout. I've taken the most high-yield questions and answered them in video format so that I can take you through why certain answers are correct and others are not.
Happy studying,
Michael
#radiology #radres #FOAMrad #FOAMed

[@shirindavies3669]

I LOVE YOU! seriously, I have been working in MRI for a while and no one, no one has explained FE and PE the way you have. What an amazing talent. Thank you for sharing the fruit of it with us.

[@radiologytutorials]

Thank you so much. You’re too kind 🙂

[@heddaisbingingyoutube]

I can’t thank you enough for these videos. Each time I start on a new video I think "this is where I will get lost", but somehow your explanations never fail to make me understand! I wouldn’t have made it through MRI exam preparations without these videos. Thank you so much, you are great at teaching!😊

[@Therealdrstrange]

Really waiting for CT videos to be released 😊

[@MRI197]

Wow thank you this is the most amazing series! I’m an MRI tech and I’m still learning and trying to understand this on a deeper level for my work! This video series has helped me more than any other lecture or test or book I have read. You put things into perfect detail! Simple and understandable but so informative! You are a great teacher and have such a gift! Thank you for sharing you amazing knowledge on MRI with us all! I know it has helped me tremendously already!

[@radiologytutorials]

Wow! This had made my day! I'm so glad the videos have been helpful. Thank you for taking the time to write such a lovely comment. Really appreciate it 😊

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.

[@shicksr1]

I share all your videos with my classmates Thank you so very much ❤

[@user-mw2wn4ix2s]

This section was a bit difficult ... watched the video 8 times to understand it properly 😅...
Thanks Michael 👏

[@deutschkurdischesFleisch95]

I have given you a subscription so that I can show my gratitude and that you really go to a lot of effort to explain this in detail. Many greetings from Germany🗿

[@424Louis]

thank you very much dr, this is the best and clearest mri series i've ever watched

[@radiologytutorials]

That's so kind to say! Glad you're enjoying the series 😀

[@remmaria]

Thank God I found you! I have been struggling to understand some points that didn't make sense for years and now everything is much more clear to me! Thank you very much!!!!

[@radiologytutorials]

I'm so glad! Thank you for a lovely comment 🙌

[@JojoJojo-er6li]

Excellent lecture! 😊

[@fathimathneena1665]

Thank you so much. It's very easy to understand the topic. You are amazing 😊

[@ariyaihalevi8180]

This stuff is awesome! You have such a talent for explaining things

[@Ruth_Grace]

Thank You! 👏👏👏👏

[@chrisdao]

These videos are really well done! thank you for providing such quality content for free :)

[@madchen.roentgen]

I can't explain how much I love you !! Feels great to finally understand this T_T

[@pvbb7893]

Thank you so much for the great content and for finally making these topics comprehensible for everyone. Greetings from a radiology resident from Germany

[@radiologytutorials]

Thank you! I appreciate it! Greeting from South Africa

[@user-ne7yc6yl7c]

Thank you so much for your Videos. I think by far you create the best radiology-related content.

[@radiologytutorials]

Wow, thank you. That's very kind of you!

[@aleenajoseph6633]

Wowww.... thankyou so much sir!!!!

[@khizerahmedkhan1812]

You are the best man. A life saver. Keep up the great work.
I am radiology resident from Pakistan.

[@radiologytutorials]

Thank you. Appreciate it. Greeting from South Africa 🇿🇦

[@gudurisuresh7431]

Thank you doctor 😊

[@radiologytutorials]

Most welcome! ☺️

[@DrZubiaTarar]

Thank you Sir.

[@radiologytutorials]

You are most welcome Dr Zubia

[@merlo986]

Amazing❤

[@radiologytutorials]

Thank you! Next video drops tomorrow 🙂

[@sohailkohri7269]

Thankyou sir🙏🙏

[@radiologytutorials]

It’s my pleasure Sohail 🙏🏻

[@lucaya]

Amazing lecture

[@radiologytutorials]

Thank you 🤗

[@fantasykidz86t]

great dr

[@radiologytutorials]

Thank you 🙏🏻

[@Dimapolymerclay]

REALY AMAZING, Can you please help us to explaining the other different sequences like GRADIENT, SWS, MRA, etc

[@radiologytutorials]

Thank you! Starting pulse sequences next week 🙂

[@Dimapolymerclay]

vielen dank @@radiologytutorials

[@billyidolman4666]

Does each digital cell in the generated frequency encoding row represent the aggregate signal from that x-axis point over time of does it represent what that axis contributes to the overall NMV at a given point along wave?

[@user-zf9so6zw9e]

Thank you for all your amazing work and making this available! Its been very helpful in trying to understand this complicated topic for my registry exam! Do you have the question bank availble for MRI yet? I would love to do that in addition to your videos to make sure i am understanding the material properly 😊

[@radiologytutorials]

So glad I could be helpful! Busy working on the question bank right now - hoping it'll be available soon 🤞

[@user-nr6qf1pj5l]

Hej Michael, thank you for a great video! I got confused with one artifact which occurs in the frequency encoding direction: Zipper artefact. Why it is located in the row not a column. Creating one straight line in the row. It should be horizontal if it feels up column (x axis direction?)

[@aakib_parray1470]

When gradients are applied before rf pulses or at the same time.. If at the same time the how can we match the precisional frequency with rf pulse as body is Expercing same magnetic feield ..

[@sohailkohri7269]

❤️‍🔥❤️‍🔥

[@sanawarhussain]

Hello! I found the tutorial to be great, but I am a little confused. Isn't the "inverse Fourier transform" used to convert signals from the frequency domain to the time domain? If that's the case, then shouldn't the transformation from time to frequency be called the "Fourier transform" instead of the "inverse Fourier transform"?

[@julianpinn5018]

I agree with you. This is a Discrete Fourier Transform and not an inverse FT

[@kayk928]

when the FEG is turned on and there is a difference of frequency along the x-axis, this is all happening simultaneously with the protons all rephasing/dephasing from the 180 RF pulse? It is easy to visualize it separately but difficult to visualize them happening simultaneously.
I'm not sure if my question makes sense but when the FEG is turned on, it seems we do not take into account the protons that are being influenced by the 180 degree RF pulse.

[@radiologytutorials]

Yes, you’re right. This is extremely difficult to visualise the processes happening simultaneously. The reaccumulation of transverse signal is occurring after the 180 degree RF pulse (generation of a spin echo). When the FEG is applied, the frequency difference along the x axis causes phase incoherence (and loss of transverse signal). This is why we generate a gradient echo at readout - hopefully the gradient echo talk will help with this. The processes are happening simultaneously 🤯 It’s a miracle we get any usable signal..

[@KreativeChaos716]

The frequency encoding direction is not always on the x-axis it can change from x or y depending on your scanner correct?

[@radiologytutorials]

Correct. You can chose the frequency and phase encoding directions. Just use the label x axis by convention 👍🏼

[@milenaditsova2801]

my brain exploded

[@user-xm6su9sf8z]

💝💝

[@markhajas]

At 19:25 you said it's an inverse fourier transformation but what you are explaining is you are converting time based data to frequency based data. Isn't it actually a normal fourier transformation? The caption also says it's a normal fourier transformation.

[@tysonbrown543]

The inverse Fourier Transform is used in image processing, where it is used to convert images from the frequency domain to the spatial domain

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.

[@suhanakohri8928]

🥰🥰

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.

[@BingLi2021]

Thanks Dr, love your videos and admire your knowledge and great explanation.