Introducing MRI: K-space: Features and Tricks (24 of 56)

www.einstein.yu.edu - The twenty-fourth chapter of Dr. Michael Lipton's MRI course covers K-space: Features and Tricks. Dr. Lipton is associate professor radiology at Albert Einstein College of Medicine and associate director of its Gruss Magnetic Resonance Research Center.

[@jefferson6449]

Michael Lipton on 1.5 speed is a spiritual experience for me

[@natjimoEU]

i know right, im learning at such a fast speed

[@kawarpalsingh6812]

You are a gem. These are the most excellent and priceless lectures I have ever listened. Thanks a lot Professor.

[@tadasdidvalis3246]

Finaly! Finaly an explanaition why k-space amplitude is highest in the center and dies out towards the edges. Thank you!

[@rjr287]

This lecture series is awesome for radiology residents, thank you for posting

[@michaelkramer8601]

I wish I would have found these videos before I passed my MRI boards. These videos helped explain several concepts that I lacked proficiency. Might have to go and watch the whole series to complement the sources I read on my own.

[@ivanradovic2916]

Priceless.
Thank you, Dr. Lipton.

[@joemo4104]

You did such an amazing job in explaining all this thank you so much for this whole lecture! I'm currently going to university in austria (radiology technology) and you helped me out so so much!! :)

[@SM-ls6rw]

It's my understanding that free induction decay or T2* curves now do play a large part in imaging (for instance, iron quantification in the liver).

[@effiongjay373]

Such an important series and so well presented. Thanks Dr Lipton and I wish there's a series like this for CT. I'm a radiography student from Nigeria and these lecture awakens my interest in mri. Such a priceless piece.

[@e13mtke13mtk]

this is an incredible resource! thanks again!

[@vijayawankhade9886]

Thank u so much sir...ur teaching style just awesome..thank u

[@satchelmcleod6040]

Awesome job!

[@yongkailiu1448]

Really great teaching!!!

[@user-zb8nw1py6k]

It is very helpful lecture. Thank you professor.

[@mihaimoldo]

One question I would have and i think nobody asked is that, are there multiple k-spaces for all the slices or just one k-space for the whole sequence ?
I mean when you acquire 30 slices on the head, does the computer use 30 k-spaces or just one for every bit of information /signal?.

[@fossegutten6579]

This man is a genius

[@ChokeArtist411]

@8:24