K-space MRI Explained | MRI Signal Localisation | MRI Physics Course #10
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- čas přidán 9. 07. 2023
- High yield radiology physics past paper questions with video answers
Perfect for testing yourself prior to your radiology physics exam 👇
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The representation and explanation of k-space here does not include scalar vector and 2D frequency contributions. This is beyond the scope for this lecture series. There are many good (albeit, long and involved explanations out there for those who are interested). I truly believe this level is enough for junior radiologists and radiology technicians learning k-space for the first time.
K-space can be a difficult topic to understand. Learn how we fill k-space and which parts of k-space are responsible for different image characteristics such as contrast and edge definition. I've tried to keep this as basic as possible. Sharing just enough information to allow you to understand how different pulse sequences can use k-space characteristics to their advantage.
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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
Mike: after 6 years studying I have finally come across the finest content i've ever seen online. My sincere congratulations.
Thank you so much @ericcummings29 🙌
The hero we have all been waiting for!
Mike. I'm soon starting my studies as an MRI Tech and your content is some of the best and most informative I've found.
It will likely prove invaluable to me and others. Thanks for your brilliant work!
Great to hear Adam. So happy the videos are helpful!
Thank you sir, you are appreciated and I hope 2024 blesses you just as much as you've blessed those you've help with these videos!
I have watched all the MRI Physics videos you have while I study for my ARRT and you have made it SO EASY to understand these topics. Thank you!!!
정말 명강의..최고에요ㅠㅠ
I cannot believe that I found the best tutorial on this topic. Thank you so much!
And because of you Sir Michael, I have understood K Space and the videos before this. Going now to the next video. Appreciate your time and talent and your crew for putting these videos together.
Thank you so much for such a lovely comment! So glad you've got K Space all sorted 👍
Really incredible work dr Michael Sir,clearing tough MRI concept at our basic level🙏
So glad it’s been helpful. Thanks for your support!
What a great explanation.. keep up the good work 👏
thank u so much for the tutorials..after reading Farr's physics and listening to your lectures, i have more clarity now ..thank u again!
So glad they're helping to supplement your reading 😊
Thanks Mike! You’re saving us all out here with this amazing physics and anatomy content! 😅 hope you’re doing well and keep up the great work
Nadir! How are you mate? Good to hear from you. You writing this month?
@@radiologytutorials all good and you? Yeah gonna give it a shot next week but was a last minute sign up so will see how it goes - your videos have been a true life saver 🥹
Yeah. I’m good thanks. If I can give any advice. Spend as much time on anatomy as you can 😂 it’s hectic 🫠 Shout if you’re in Cape Town at all. Would be good to grab a coffee!
@@radiologytutorials will definitely do so! Thanks for the heads up man
Thanks dr michael looking for the next part
Thanks a lot sir Michael, 🎉
What an awesome teacher ❤
Thank you!
Waiting for your new video,,, thanks a lot sir Michael
Cheers Fazal 🙌🏼
Thanks doctor 😊
When I was an neuroscience major undergraduate, I was always arguing with my physics friends about who’s major is more difficult, and now I have to admit that physics is harder.
Haha, totally depends on what you're studying in the field. There are so many unknowns in neuroscience and physics - but I agree physics can get pretty abstract very quickly 😅
Great Thanks Dr.
Most welcome!
Thanks a lot
Thankyou micheal🎉🎉
My pleasure ☺️
Superb...
Thank you Jegan 🙂
is k-space higher for higher T (7T and 10T) MRI?
Thankyou sir🎉🎉
Anytime 👍🏼
Thankyou sir❤❤
Pleasure ❤️
Nice content. But it's better if you add some captions, B-rolls, or pictures to your video. BTW did you know someones who needs a video editor?
Thanks a lot micheal please also make videos on ct also 🙏🙏
Pleasure Sohail. CT will be coming after MRI 🙂
@@radiologytutorials thankyou so much sir
For How long the q bank is valid when purches it and How many Q in both ultrasound and x ray... I guess if you post a sample Q on the web page would be better.... Thank you for amazing material you freely give us
Once purchased you have access to the bank for life (including new questions which get added). I’ve purposefully only included questions (or question themes) that have come up multiple times in past exams - to ensure they are high yield and not making people focus on unnecessary details. Both banks are split into 7 sections with 5MCQ, 5 true false and 5 short answer questions. I then have videos going through each question explaining the answer with diagrams etc. Hope that’s enough info. Thanks for the suggestion about including example questions. Working on a new design as we speak!
Great video!! My one doubt it's when obtaining the Echo signal (then digitalizing it) lets call it S0[n] for first line (=0), whe should apply a FT before filling our first line of the K-Space matrix right? I think video suggest filling line just with the amplitudes we obtain from signal in time domain, and that make me doubt..
Hi Tom. Yes, great point. We can store data in either the time domain or frequency domain. In MRI we use the frequency domain (ie FT prior to entry - therefore data points in k space represent spatial frequencies). In my attempt to make this have no math I have definitely not made this clear in the talk. And unfortunately I’ve perpetuated the time domain filling of k space throughout this series 😅 yes, it keeps me up at night. Might need to do a more comprehensive k-space video once I’ve completed the series!
@@radiologytutorials I was going insane trying to figure out if the horizontal axis represented time or frequency. Thankfully I found this comment and my worries can finally subside. :)
Great video, as usual. Are you going to explain Fourier transfrom or this math is too difficult to our medical minds? 😂
Haha 😂 great question. I’ve been debating this. The way I have discussed k space here (by omitting 2D sinusoidal waveforms, both real and imaginary, as well as phasor vectors) means a detailed mathematical description of Fourier transformation would probably be out of place. Having reviewed many past papers the the level of question asked in radiology is FAR below that level of detail. The understanding that sampling of signal over time can be Fourier transformed to x axis location based data and that a combination of this data and phase encoding steps can be used in one large >65000 variable simultaneous equation (also not exactly true) to calculate pixel values is probably sufficient 🫠 once I’m home I’ll send a link of an excellent CZcams video with most of the math 👌🏼 be warned it’s not for the feint hearted 😅
i almost thought i wasn't that stupid until i stumbled across this video... good grief
why does your k space have time as an axis? it's supposed to be frequency domain, so clearly something is very wrong with your explanation
Each point from a row in the K-space matrix is a digital sample taken from the actual analog signal generated from the selected slice, so as the time passes, you fill a each point in a row from left to right, so it is correct to show the time axis along the K-space; I believe this is the meaning behind the time axis.
@@mihaigherman3713 so the whole k space represent one row in X axis?
Keep it up but videos are too long
🫠
Thankyou sir❤❤
My pleasure Mehboob 🙂