Love it!

Thank you so much! So happy to hear it helped demystify the whole phase encoding thing!

Honestly comments like these are the greatest reward for making these videos, happy to hear it helped make things click. Credit to MRIQuestions.com and Dr. Elster for the underpinning theory here, I just expanded on it a little :) And while the real picture building process is a little more complicated, this ties in well with the typically taught base MRI physics concepts while avoiding the math. If you're really curious to how the real thing works, stay tuned! We will have a full series on it in the future including K-space.

So glad it was helpful, have a lot of new material in the works so stay tuned!

Me too 😂

Thank you! Yes the whole algorithm thing has been frustrating, it seems like no matter how many subscribers I get or how much I advertise on social media, every video is just a slow creep from the moment it's released until it slowly makes its way up the ladder with views and likes. Maybe KZfaq isn't a fan of my jokes 🤷 But thanks for commenting and please do share with anyone you may think would find these helpful! Good luck with the exams!

@@MRIPhysicsEXPLAINED Thank you very much, my whole year already watched your videos, so dont worry, you'll get there eventually 😁

@@mateuszskrzypczyk3563 Awesome thanks!

Thanks for sharing and supporting and cheers from across the pond!

Thanks for the support and watching, happy it helped!

So happy to hear it helped and thanks for supporting!

Hard to be the new kid on the KZfaq block. But liking, commenting, and sharing the videos will help spread the word, thanks for the support!

So glad to hear, good luck on your exam and let me know how I can help further!

More are in the works!

You're very welcome and glad it was helpful!

Happy to hear it helped, thanks for the support!

Haha in the works, thanks for the support!

Thanks for watching and commenting!

So great to hear and happy I could help make this process a little more clear and hopefully entertaining! Check back tomorrow for the latest video!

Thanks for commenting and supporting the channel!

Thanks so much for the comment! I definitely have a whole set of lectures dedicated to k-space and how we truly build an image which involves getting into the math but I think I can present it in a visual heavy way still that will be intuitive. Not sure how deep we'll go into Nyquist theorem and such, always trying to find that balance between keeping it understandable without going too deep into the weeds but we will see! We very briefly touched upon the idea of Receive Bandwidth, I believe in the frequency encoding lecture but if you have more questions please send them my way! kzfaq.info/get/bejne/er-aZLZ9s9bUgYE.html

My pleasure! If you're interested in more physics/radiology education, check out our new project radiofreedia.org (work in progress)!

Thanks for supporting! Check out the new video that just dropped today :) kzfaq.info/get/bejne/Z9Kara-b1s2zd5c.html

Glad it helped!

Glad it helped, thanks for commenting and supporting the channel!

Thanks for the support!

Thanks for watching and commenting!

Thank you for the feedback! These lectures are meant as a way to intuitively get a grasp of how we build an image and what phase and frequency encoding are while avoiding all the math which is not insignificant. So this is more of a working framework to get a good base understanding from, but not an exact explanation and I encourage you and everyone to think critically as to how this may not explain the full story as a technologist or radiologist would understand it knowing the depth and variations of the sequences we perform on a daily basis. The full, complete explanation will be covered in future lectures. Stay tuned!

Welcome!

Thanks for the sub and supporting the channel!

In the works, thanks for watching!

Thank you!!

😂

Glad it helps and thanks for the comment!

😁

Love this question. The short answer is yes, this the classic teaching you will find. But this seems a bit... unrealistic doesn't it? Unfortunately, to understand what is really going on here, we need to dive deep into the math governing image reconstruction which we will do in future videos :)

Most welcome, hope you found it useful!

Hello, check out the lectures on slice selection kzfaq.info/get/bejne/rJ6aipt8lt-Re3k.html and frequency encoding kzfaq.info/get/bejne/er-aZLZ9s9bUgYE.html where we go in-depth on how to localize the signal in the Z and X dimensions in you haven't already. If you still have questions let me know!

@@MRIPhysicsEXPLAINED I'm confused about why we don't get the same problem at 7:55 in the Z-X plane. I can see that using frequency gradient in the X and Y axes causes the same frequencies to repeat and thus we can't resolve along (x+y=c). But why do we not get the same problem when using frequency gradient in both the Z and X axes? How are we still able to resolve voxels along those diagonals?

The beautiful thing about the slice select gradient technique is that we don't have to resolve the signal in the z direction, the gradient is turned on along the z-axis so that when we apply our RF pulse and tune it to the region of the body of interest along the z-axis, we know all the signal we receive is coming from that slice alone. We simply just then turn off the z-axis gradient, the protons in the slice fall back into precession at the Larmor frequency, and the problem then turns simply into localization along the x and y axes for which we do the frequency encoding and phase encoding techniques. Now in 3D MRI acquisition we do replace this slice select gradient technique with a true image encoding gradient along the z-axis, but that will require a little extra knowledge to understand which we'll cover in future lectures 🙂

My friend you are way ahead of the learning curve! The core lecture series is developed for the everyday radiologist and technician who wishes to get a feel for MRI physics without getting into the math which is multivariate calculus level. This expands on the concepts taught in most paid MRI physics courses, and as you have pointed out, what is the point of K-Space then? This is why K-space can be such a confusing topic in these courses, and in order to understand it and how we truly build a picture, we have to dive into the actual mathematics governing MRI image generation and we will do that in the future advanced series :)

Wow thank you so much, it really means a lot!!

Good eye and I debated on what is the best way to portray two gradients simultaneously on the image because it definitely can get confusing. I decided the most accurate would be to orient the addition and subtraction based on the axis the gradient is applied across. If you look at the X axis gradient, it is below the axis on the left (subtracted from B0) and above the axis on the right (added to B0). If you now turn your head 90 degrees counter-clockwise and look at the Y-axis, the portion of the gradient along the Y-axis in the bottom left voxel is above (added) and below in the top left voxel (subtracted). Hope this helps!

@@MRIPhysicsEXPLAINEDI also have the same query… not convinced by your answer 🤔🤔… u said we should turn around our heads in counterclockwise direction to see the y axis gradient… why not clockwise? In that case we will find +By in the top voxels and -By in the lower ones.. following the same rule as for the X axis…please explain.. thanks

@@rubyamir5245 Hello, sure you can turn your head the opposite direction on any coordinate system and the sides will be flipped, but mathematically you essentially get the same result albeit a change in signs. The important point is that we are creating a linearly changing magnetic field along the Y-direction of the slice, it does not really matter whether it is increasing going down to up or up to down.

Didn't know the former president was such a big MRI physics fan and I apologize to the nation for such bad jokes! 😂