i think is to come "'cause" to come here if you can still hear me from here a a small enough room should be easy so a medical imaging an image analysis uh a really is uh it a topic which is so very widely used in the routine clinical practise these days and they especially image acquisition part has a revolutionised the might is in a uh today uh a probably out of a of that the X rays are being with us from more than a one hundred years and that uh first of accidental a medical image of of of missus run again uh uh was not in a ninety five and uh after that the right of different the a you mean you wanna only this sorry there exist that but is uh i no x-ray ct was magnetic resonance imaging with a was that are emission tomography with a single photon shouldn't no tomography with optical coherence tomography and that out of similar more these which are used to really widely and uh and they them many ways uh have changed the way how physicians do the madison and that many ways a you know the physicians are virtually unable these days uh do uh function as the used to uh even ten or fifteen years ago the an existence or medical imaging cut is really heavily depend then on the advances in the signal processing and that that's why V be invited to a present here and to to string some the ties between the signal processing community in the medical imaging community would the ability uh yeah to image in people biological structures is uh uh uh true dependent on the signal processing the the signal processing is making a the the in a blink uh engines uh you know behind the scenes to get the images uh i in two D three D four D and and a five D routinely these day so the three D image is probably obvious or at is it's a three-dimensional volumetric image which we get the for D maybe a little a little tricky so if you imagine you know a a beating heart uh that's a three dimensional object which are has the force the this time and uh now you maybe even trickier able to five B may mean so imagine the beating heart uh which is a four dimensional uh and to the and then you do the imaging over time for example every week on every day and you could the films the you know the imaging and that that's probably uh the suspect to dimensionality uh how far you typically get older you can think about that combining multiple of D imaging can images and the and the go to the higher D's uh you know and that the that matter there are two uh main ways how you can i didn't you can acquired the images uh maybe one of those uh one possible distinguishing fact would be very are rising ionising or non housing addition X ray being the ionising radiation of course uh for example E um you know i'll just some big not ionising still or you may have passive if listening to signals like a they don't so i think a your you're more like you was uh uh in some ways and listening to do the results are like in M mr let's talk a little bit of bottles individual imaging modalities uh and uh you know one of them maybe maybe do to one a very exciting ones of course is the x-ray ct which is very routinely used for three D and four D uh imaging and that the image a reconstruction the the formation of the image is heavily depend then on the radon transform and and similar transform which you can do oh so the image reconstruction is not from projections and uh it's uh oh obtain from their you think x-ray beam there are many advanced the reconstruction techniques and of you hear about the some of them today uh from a michael or and and you rang uh including the multi beam scenarios and than found beam scenarios and someone the recent recent uh x-ray imaging is combining multiple X source is a multiple x-ray detectors and that those uh source is and the text as our day thing in the uh a very high speed around the body was about point to eight i think is the highest the current speed the available in the in the commercial C Ds as the extra scanning speed actually exceeds forty centimetres per second which means that you can uh image to act chest the uh a region of a human body in less than half a second to you can't the entire body uh image about five seconds which clearly is causing potential problems with the patient leaving the table if you stop the scanner and the no just starts getting because the speed of the of the uh you know a card uses so so far so it one example i also try to show some examples of the individual limit what of the images this is an example of a roughly a domino uh part of the human body you can see the the spine in the middle um you you may be able to see some of the uh some of the vessels uh which you can have here and that uh you can identify the inner and outer uh walls of the vessels well for example if you look at this particle i we can see that but being to white part of this this uh a green area being the to wall and really we can difference between this particle slice and that's lies it seems to have a normal wall seems have some additional material uh inside of uh of the room in a wall which are if you image in three D will find out is somewhat from baltic area uh in this uh in this location and that a something which should not be there from in your is more changes it can be you by X ray D in this case a some contrast that will being included in the in the book oh example from the x-ray ct these the example from the long imaging where we would have one slice or of the make the uh uh mid level of the long uh you can see the uh the left and right long you can see the individual features here like this portion here this portion there which uh divide quite nicely quite visibly the individual so of uh of the long and of course you can get a sweet michael are presentation of lungs with the colour coded the all right to identified a back to that little bit uh if you talk about E mr imaging again it's three D forty the imaging modality which uh uh start with the high strings made tick feel that lines the minimisation of the hydrogen atoms water and uh you of boy some a radio frequency also which would core use form the whole dating the tick that and that this of can be detected by D M are scatter and then us and that you create we need a sense a different all some very complex signal manipulation to get that was in view images but the images are quite spectacular so in this case a you can see the example of the cardiac and is is the beating heart in the different projection to a short X is long X image uh uh of the left and the right ventricle so left and right but suppose here or you can also go uh so was a slice of like a short axis lies which should go no from the valve of all the way down to the a set and that you can see how it looks a uh a three do might for the and the asked like a face or a and cyst like face it would the like station and the screen is uh of the hard to it's a lot a a way how you can image do the same area of the body and that you have the hard which we so before like here but you have a different the direction of uh of your slices and this case on the left and side you can see D left ventricle out fault tracked with the aortic valve in this part you see what is called a candy cane uh the christmas you can to came uh you where a you see the or that quite nice still do i way out uh to the that if an example of mr imaging curve from the area of car a it's a from the neck area where in the uh bought for uh uh vascular a image you can see that this ten is the narrow incur of the vessel right here and that uh you can look at in the view cross section so off uh all the vessels if you look for example at the two different cross sections like a in this yellow and an orange areas you will see that that there is that that car date that uh right here with a little bit thicker wall and that that's well a good thing but it's not that super bad thing but if you see on the on this difference lies a slide that you sure by orange that that the room and start be really late i that and that you are getting very close to having a true problem and that this uh a find would be a source to strong uh which which clearly is not a a joyful think that have uh are you know don't have to image or only the cardiovascular system is another example of the knee joint the imaging what you have the the femur the a T V and about that one here you can see the bone structures as well as the individual portions of the cartridges which uh uh which you have you can analyse and the uh again shows sold just like if you switch to the ultrasound the and the old D optical coherence tomography images again we can easily do three D and forty uh imaging the ultrasound is using ca uh of of sounds uh of a different frequencies frequency the frequency influence the resolution of the imaging as well the depth of penetration of the signal but a money whatever T i know that you can again use it for a variety of uh best Q and the you'll be jane uh uh i don't techniques and so you have to go coding the model or face in some way similar to the ultrasound uh uh it uses different signal processing cut approach is with the coherent light uh it allows uh to a choir images of very high resolution uh based on the uh frequency laser uh maybe a hundred and a a one micron and that therefore lapse of penetration of we'll all but it's of it's fess found uh very fast a fascinating applications of non a six three D imaging view of the red in a and the core black cat uh from the inside a a interest vascular image i the example the ultrasound sound some a two D has slice is uh you can see the individual of use uh you know the heart you can also do a imaging what is called a real three D echo we four dimensional model the where a the and entire three D volume is acquired at the at the same time of the real time we get for example compared to D which is a don't not perfect that is respect to noise with a three D which is even rest picked to because you have uh a little bit less time to do all the audio an example is uh coming from but uh in geography imaging interest lots of sound imaging a that on the on the left and side that uh i can start okay level inside you had the x-ray projection of image with the not the K area here you can in they call that it with the intervals ultrasound sound that for on the tape which all dates that that thirty frames per second you can get the imaging if you put back the cost are uh use of can get a dimensional image or a of the current are three you see the vascular structure to the the any here this is the or itself as well as the the black which is uh a which may be uh it all okay the in in the corner this is an image or from the retinal channel uh all C uh uh image or of the macula oh so for the visions body use the for we have it's is that in the nation the uh a location but really see sharply this C D optic nerve had the blind spot though of the right a it's very interesting to identify those individual layers and start to associate the think is of those in the you or so with a um individual is easy which at which so the signal processing in image acquisition is uh use the very broadly and that uh clearly the advance is uh and the complexity of signal processing pipelines are absolutely critical for uh medical imaging medical image position we are trying to get heist image quality a high speed of acquisition highest resolution that's all what signal processing is gay uh a a question which is here is a how to get the high school of the images is minimal goals of and we are working with ionising radiation again a challenge the signal processing community and that something what the what be have need the uh to be able to use uh the imaging the best oh i made a statement and the very beginning that that uh image acquisition has revolutionised the critical uh portions of the madison the image analysis has not and that image analysis is a a cold in medical image analysis is widely used as research applications lights not for fully enter the clinical as it's to in clinical except and and that yeah robert but a can i it's of corn there is all the first one it really would you use the in the in the quantity matter uh it's also used for a screening in the cardiovascular matter in of tonic uh imaging matter and so on so for example if you can could occur it into a media thickness measurement is it the car the are three now image the uh with the ultrasound you to to stick this of the wall is the in a bright here the media layer you in black and that i can start analysing the thickness of the wall and that you can uh measure what think is it and the this case the thing it's of the new a wall this one would be but i have a many be a point six million you here you may have a different a subject that body measure to think it's of the wall to find out of stick this is actually about the many meter for the farm now the question is what i me and uh you can look at norm at if uh a a so of normative data is a a uh uh of uh of patient is respect to a H you may find out of for example complete normal while the second example is actually think wall and some person it'll will be a high risk a of uh but a heart attack or stroke a uh sometimes later in life and the uh maybe be ready for uh uh or some a drug treatment that uh a in something i showed do some of the uh images image is all the or to just to give you an idea how the analysis looks like uh you can get a three the actually four dimensional a analysis a three D plus time of the entire aortic blanks this respect to cross sections and motion and again gain compared to a a normal values maybe some values of uh um of uh subject to with some E real three D echo he's C D image back here i K i all that you can see those also those red calm to was on the right hand side in automated analysis which a also you to get maybe to uh volumetric metric information we the cardiac cycle partly ejection fraction what meant not on the base on the area and a area from a uh x-ray ray ct uh from the image of the long you can get the entire at every rate be analyzed you can a use it for uh for of image guided the surgical makes you want to reach some location of a you know how to get there you can uh do to separate the noise is one do you all and and you segments of the long uh a you probably here bit more about that uh we do have uh i don't a we have for context stress analysis uh uh for the for the me again image show showed you before where we identify individual balls identify the cartilage locations and that based on that you can cochlea in view by mechanical stress so which are applied to a individual subjects a uh being included in that uh imaging which oh of course you don't image only hear men's we image uh animals as well including small animals so this is an example of a models this is the most long for the mike C you scatter and the uh a reconstructed that three dimensional uh at a rate the of the mouse which uh uh seems to be an important thing or example from the malls uh with a three D C give registration many or image the same also over time you to register the models uh images uh so that you can find out where exactly the same point was in different scans or you like to it'll get a made use a like a later uh uh for different my this is the example of the analysis off that the macula make or image at uh from all C T in you can see we identify a large number of individual layers which are uh are are able to identify uh get the link use with uh uh are be is for example and some other uh disease i have one example whole for visualization a guide intervention here uh from the uh from the a uh surgical planning so traditionally you are planning on the on the two D display and uh you can also do the surgical i think in the virtual reality and wider and that you like to have like the three dimensional view and this is a a short movie that swap shows uh uh what would be interesting visualisations which are you have down to lie about together with the across university of technology incoming still grad you see the labour uh being ca three D visualised with the uh vascular trees and the tumour does the as the green thing here is the is the cancerous tumour which needs to be a sector so you have to identify yeah the individual segments uh in the labour the images themselves are actually displayed that us to do some i transparent goggles we the surgeon is uh is varying and that the uh oh this is which you see here is really interactive uh panel which allows you to project the individual a sections all dct in the proper orientation uh by all this place through the uh sort of got so an example of the uh of the best three here you can identify and of you portions sort the vascular tree and that as a result of that that you can get that yeah segmentation all the ever in the segment because when you want to re sec portion of it we have to recite the entire segment you have to do the segmentation as you will see uh C immediately uh uh after this and uh a a a you can you can use it then actually quite useful for the more difficult the a a sections than uh do ones which are so really T you uh as get the lost the last second of those in you light sleep segments once you have that you can start to uh starting planning for the for the and the are sections you can get a a or was in the segments gets a i see that to M or i know that the oldest this particle segment has to go so what sort of surgery a just take it out and that find out what happens if you do that do we have enough safety margin between the two oh such should uh have to this uh a short introduction it will consist of five different uh uh a papers it a uh try to give you all some overview of the entire chain of typical operations steps and the first uh a present they should be given bit by michael ones are beginning with the image reconstruction interior tomography from by medical applications be the topic of the second talk uh image and signal processing challenges in the translational uh likely imaging research a given by all really if felt then a talk above field you signals for respiratory gating long C image sequence by uh joe right hard and last one be how we can model at the origin a the a populations given by so this was a very brief introduction i think we are the end of my a all the time and that if you have a one quick question i can answer or otherwise you problem be able to as a question get more detailed uh or right that's why whole right right