hi learners it's em from sauna nerds and this video is on unit 15a image processing and contemporary features unit 15a image processing and contemporary features in unit 14 we learn that the image processor is home to the a to d and the d to a converters as well as the scan converter we also briefly cover the concepts of pre and post processing unit 15 has been split into 15a where we're going to learn about the different image processing features and contemporary features and 15b in which we'll learn about image processing features and their effect on spatial contrast and temporal resolution for our fourth discussion on resolution section 15 8.1 image processor the image processor receives scanline information from the signal processor which we also knew as the receiver now at this point no image has been created all of the information is still just a long string of data representing single scan lines so kind of like what we have in this column here all we're getting are just rows and rows and rows of information about how these pixels should be coded with their digital numbers now in the image processor the information becomes digitized saved into the scan converter and then switched from its vertical format like we see here into a horizontal format that the display will be able to use now when the scan converter fills its matrix with pixels that is one entire frame and then that frame is displayed on the system display or the monitor the idea is is that this whole pixel matrix is going to be filled at least 30 times per second to create what we perceive as real-time imaging when the scan converter is filling the matrix with data the machine is writing and the scan line data is continuously written over and over as we are live scanning to refresh that image as we see it on the display now during the writing process we are changing the image we're changing our gain changing our compression using our tgc's all of those various tools and machine knobs are going to be pre-processing functions that is because they are occurring on a live image now when we freeze the image the scan converter switches to read mode and this means that the image can no longer be altered with those pre-processing tools the data displayed is just what it is and if we alter anything at this point it's a post-processing function a really helpful way to think about the pre-process and write mode versus post process and read mode is to think about an author now when the author is writing their book they can change it all they want they can rewrite the story they can change the character names change the settings but once that book is published the only thing to do now is to read it so the machine is actually doing kind of a similar thing in its memory as the rewriting is occurring in the memory it's going to create new frames that can be altered with one of our really many pre-processing tools in a sense we are changing the story but once we hit that freeze button the memory is no longer accepting new data and is only available for reading that data that is saved in the memory at this point can undergo post-processing changes but the trick is is that we can always bring those post-processing changes back to exactly where we started from because that is what is saved in the memory during the writing process we can truly never get back to that original data because again it's always been written over so in this unit we're going to talk about quite a few imaging processing features so i want you to take note is it a pre-processing or post-processing feature and then also some other contemporary features that we have in our machines so some of our features are going to include magnification fill in interpolation b color panoramic imaging spatial compounding temporal compounding frequency compounding frequency tuning coded excitation edge enhancement elastography cardiac strain imaging 3d rendering and then harmonics and dynamic range are both going to have their own unit but are considered image processing techniques so we actually have quite a few topics to go through to complete this unit while we were going through the topics make sure that you are paying attention to really what the definition is of that feature how it improves the picture or what its goal is and then note if it is a pre-processing or post-processing tool section 15a point 2 magnification so magnification is also known as zoom and it's going to allow the sonographer to create a larger close-up view of the region of interest which is often abbreviated down to roi region of interest zoom is controlled by a knob or button on the machine and there are two types of magnification right magnification and read magnification right magnification also known as right zoom happens while the image is still live so this is a pre-processing function to understand how right magnification works let's go ahead and look at these six steps so the first thing that's happening is that a live image is being acquired by the machine so we're scanning live if we move our transducer we're getting new images next as a stenographer you're going to select the zoom button usually this means pushing it in so you push the button in and what pops up is a box and that box is called your region of interest so as a sonographer then again you're going to resize that box and move it to where you want the zoom to occur you're going to activate the zoom button again which is typically another push of the button and then this is the important part the machine is going to rescan just that area you've selected using all the scan lines using all the pixels so when the machine uses all the scan lines to scan that small region of interest we are using the same amount of pixels and the same amount of scan lines that we were once using for the whole image now just for this tiny part so right magnification actually really improves our spatial which is detail resolution the other interesting thing about right zoom is that if your region of interest box is placed a little bit more shallow than the max depth of the image when the machine rescans your region of interest area it's only going to send pulses down to the bottom of where your boxes so instead of sending pulses all the way down to the max imaging depth it's only going to send them down to the area that your region of interest boxes so if that happens to be more shallow that means that there's going to be a quote-unquote new max depth compared to the unzoomed image so therefore right magnification can improve temporal resolution if your region of interest is more shallow than the bottom of your picture so you're going to have to do a little bit of imagination with me but imagine that this cute little puppy is moving around and we want to zoom in on his cute little nose so we're going to click the zoom button and a box is going to come up and then we can rearrange this box if i wanted to zoom on on his eye or if i wanted a smaller area i can make this box smaller bigger area i can make it bigger i can change where this region of interest is once i've selected the area that i want remember we're still live at this point i'm going to click zoom again and i'm going to get a live image zoomed in on that area that i selected all the pixels all the scan lines are dedicated just to that region of interest so when that occurs we can get really really good detail notice how we can see the texture of the dog's nose we can see the hairs very well this is awesome spatial resolution so again live image click zoom your box of interest or your region of interest comes up click zoom again after you've decided where you want it machine scans everything again uses all the pixels all the scan lines to really give you a nice detailed image here's another example using actual ultrasound images we've got on top here just a neck muscles up on the top here the box is actually around a lymph node so the stenographer was live on this picture brought up their zoom brought up the region of interest click zoom again and then the machine scanned the whole area again to create a zoomed in image of just that tiny area so right zoom or right magnification is the way to go this is what you want to use when possible use your right zoom that is because it improves your spatial resolution and most likely will improve your temporal resolution as well now i did say that there were two types of magnification the other one then is read magnification so with read magnification which is also known as read zoom this is going to happen once the image is frozen so now this makes it a post-processing function looking at these steps then we can see how the stenographer can use read zoom so you're imaging you're going to freeze your image with the freeze button and then typically what you do is turn the zoom knob before we were pushing it in to activate it and to get our region of interest this time it's really just a turn of the knob and when you turn that knob what happens is that instead of rescanning because remember we're frozen right now all that ends up happening is that the pixels and the image become a little bit larger now if you increase your image very large to the point where you can't see everything you can actually kind of pan around the image to find the area of interest if it wasn't already centered in your view so the important part about read magnification is that it does not rescan it just makes your pixels larger so when we read zoom and it just makes those pixels bigger the computer is really just reading the image information that's already in the scan converter and changing the size of the pixels there's no rescanning that occurs during read zoom so again now we've got our little puppy this time we don't have to imagine too hard we are just looking at a frozen image of the puppy now we've got our zoom knob typically you're going to push it for your right zoom for read zoom it's usually just the churn of the knob so when we turn that knob we zoom in notice how we're not getting real good detail here we're kind of starting to see a pixelated picture and again if we kept zooming in on that dog nose we're just getting very blurry very pixelated pictures so read zoom just makes your pixels a little bit bigger you can zoom it up to the point where it's kind of unidentifiable like we can see in this picture here with right zoom everything gets rescanned we're keeping a lot more of our detail information so again this is why we want to use right zoom when we can and here's the same example again we have the lymph node in the middle of the neck here this is a read zoom this is the kind of outer edge of the lymph node zoomed in we're just losing a lot of that detail in that picture so not as ideal as using right zoom our next topic then is fill in interpolation so when we are using a sector scan the scan lines tend to start from a common point or near common point and then they diverge from one another as they move towards the far field so this is going to cause gaps in the anatomical information from these areas so in this image here this is kind of what we're talking about the scan lines typically start from a very common point or like with the curve linear you know we're across the whole face here but we're still starting from a relatively small point compared to the area that we can see in that far field as those scan lines come out we start to get these gaps especially in the far field so fill in interpolation so fill in interpolation which is also known as pixel interpolation is a pre-processing function and what happens is that the machine is basically going to take a very educated guess as to what grade level the pixel should be where those gaps exist so the machine is going to perform this function on its own it's not a setting that we can change as a sonographer but the goal for the machine is to do this without us even noticing and i would say most of us probably haven't noticed when we are scanning that the pixels don't seem to align quite right especially in that far field to remember as those scan scanlines are being created and they're being digitized signed a number which aligns with a grayscale we're going to place those digitized numbers into our matrix in our scan converter when we have a gap in the information the scan converter is going to look at the pixels around it and kind of guess what it should put in that blank space so for example these three pixels up here scan line over here came up with the three the scan line over here came up with the three the machine assumes the one in between is probably a three jumping down here we had a three and a nine well that's going to take an average of the two and put a six in between so it's going to kind of take again that educated guess and fill in these blank pixels so that it accounts for the anatomical gaps that we get from the scan lines our next imaging processing function is called b color now b if you remember b mode that was brightness mode kind of the same idea but with color so we have different maps that we can use for displaying the digital data on our screen for the most part we're just going to have a default gray as our ultrasound map but you can actually change the gray map to suit your preference and that's what we have in this column here this is probably what most people are used to seeing this grey map probably leads itself a little bit more to the blue side this one's a little bit greener and what's really neat is that you can change the gray map to your own preference whatever your eye likes is what you should be using because you're the one looking at the images trying to find the subtle abnormalities in the tissue now with b color what you end up doing is activating a color mode and you can again choose what color you want based on your preferences and this is typically achieved through a knob or a button on your machine now b color is a post processing function what it's going to basically do is take those digital numbers that were assigned a grayscale all it's going to do is switch it around and assign it onto your color scale interestingly enough the human eye is actually better at distinguishing color tints over gray tints so sometimes using b mode can be extremely helpful when you're looking for subtle changes in the anatomy and because b color helps us see borders better see differences better that actually improves our contrast resolution next up we have something called panoramic imaging so if you look at your transducer and you know that the footprint is the area that comes in contact with the skin the footprint of the transducer usually kind of dictates the widest of the image can be on top especially for linear transducers so if you have a five centimeter footprint on your linear transducer the most amount anatomy that you will see at any one point is five centimeters now yes you can kind of do that wide scanning and that'll help you steer out the edges a little bit more so you can see just a little bit more anatomy to either side but panoramic imaging actually allows us to drag the transducer in one plane creating a really long image which really widens our field of view so this is really helpful for imaging vessels or really large lumps or bumps on the body where we need just more surface area covered during panoramic imaging the sonographer is going to activate this function and then they're going to slide the transducer down the body and as they slide the transducer down the body the machine is going to be acquiring scanline information and what it's looking for is scan lines that match up and once it finds a couple that match up it's going to recognize that those are overlap areas then it's going to start adding to the picture along the direction that you're traveling in so essentially what it's really doing is just taking a bunch of frames and then kind of gluing them side by side to make a really wide field of view so in this image here this is the panoramic image up on top here this is actually of a calf muscle so this is the skin line this is uh underlying fat tissues and then this is the actual muscle itself muscle under here so sliding down the calf getting this whole gastronomus muscle here this is what it looks like if we were just to have one frame one five centimeter frame filled up this one little area of our whole calf and so the sonographer then slid the transducer down the calf once it recognized that it was beyond this point then it started acquiring the next part of the information and then aligned it so it looks like it matches up and then it just does that the whole way while the sonographer is acquiring their panoramic image and so here's another example of panoramic imaging where we can kind of see how the frame matches up with the panoramic so we have again our frame matches up exactly with the linear sequential transducer face so however wide that transducer is is all the anatomy that you can see underneath it that's then going to match up with this frame here that is outlined by the white box and as the sonographer moves the transducer up the neck it's going to acquire new frames to align side by side so by using the panoramic feature we can see all of the carotid artery from the proximal to the bifurcation where it splits into the ica and eca section 15a.6 compounding techniques now compounding images refers to adding or averaging images together there are three distinct compounding features that can be utilized by the machine first spatial compounding which takes images from different angles temporal compounding which is images from different times and frequency compounding which is images from different frequencies let's first talk about spatial compounding now spatial compounding is more than likely going to be seen with our linear sequential or convex sequential transducers and so we know that when the sequential transducers create their images they create the images kind of sequentially across the face of the beam and our newer sequential transducers are capable of phasing as well so we can steer the beam in different directions when we think of it that way we kind of think of it as just helping us to get a little bit of steering off to the sides well with spatial compounding what we're actually doing is creating one full frame with all of the angles going off to one direction another frame with all the scan lines going in a different direction and another with all the scan lines and completely different angles going in a different direction so during this pre-processing function the machine is gathering a lot of scan data it's gathering it from all sorts of angles instead of just one working sequentially across the image once it gets all these scan line data it's going to add them together or average them together or compound them together so when this occurs most noticeably the image becomes smoother those angle dependent reflectors are going to be much more apparent because we're imaging at a bunch more angles artifacts are usually less obvious and the overall signal is going to be improved but because this feature requires multiple frames to be built into one it technically is adding more pulses per frame which does decrease our frame rate so spatial compounding again is going to average multiple frames taken from multiple angles it improves spatial resolution but it is going to degrade our temporal resolution looking at this example down here then again the machine is creating one full frame with all the scan lines kind of directed off to the left it's going to scan the same anatomy again with those frames directed straight down and then a third frame is going to be created with all the scan lines directed in a different direction and the machine is going to take all three of these frames add them together and what we end up getting especially in this gray area is superior spatial resolution because we were able to average all of the signals coming back from those three frames and put them together to make one awesome picture so the key part with facial compounding is that you are getting multiple frames taken from multiple angles that are then added together to create the final image and i want to highlight again that this is happening so so so incredibly fast that really for the most part we're not even going to notice it everything's still going to seem very smooth to us because the machine is very capable of creating these frames very quickly and then adding them together so we still get that real live imaging effect so here's an example of using spatial compounding on the top image here we're looking at some breast tissue this is just a little cyst in the breast tissue so we've got mostly fats and stuff lots of different interfaces of different tissue so this is facial compound imaging on you don't have really any shadows and all the tissue looks very smooth it's a really nice image now this bottom image is showing us an image where that spatial compounding has been turned off now if we look at this picture we notice that in general the picture just looks a little bit grainier has a little bit more noise to it some of the biggest things we can see is that these shadowing structures are very shadowed at this point so those are almost distractingly dark the smoothness of the image is kind of gone another big thing that i noticed this cooper's ligament that runs through here those are typically very bright and you can kind of see that it's lost in the tissue here and that's again is because we're not seeing it at different angles where we're getting that nice specular reflection from it so we really do lose some information when we can't image from different angles and then we see a lot more artifact in our picture as well as i had mentioned before typically spatial compounding is desirable for our images so oftentimes machine just has it on by default there usually is a knob that you can turn it off and when you do turn it off it actually can be very helpful we will learn in a later unit about shadowing and why it occurs and how it's an artifact but shadowing sometimes can actually really help us to diagnose things like when we have gall stones or kidney stones in the breast cancers are usually very shadowing so if we always have spatial compounding on like we do in this picture here we might actually miss some significant artifact that might help us to get to a different diagnosis so while spatial compounding is desirable and creates a better image sometimes it's appropriate to actually take it off and still do another sweep through the tissue see if there's any changes that are significant for the patient's symptoms the second type of compounding was temporal compounding and temporal compounding is also known as persistence or temporal averaging the temporal compounding is going to be achieved by superimposing frames upon one another or layering them over time now the stenographer can increase or decrease the amount of persistence typically again using a knob or a button when we use temporal compounding it's going to create a very smooth high quality image that's typically because it is reducing the noise and increasing the signal to noise ratio it most often use persistence when you are gathering color doppler images and when we use persistence with color doppler what we see is improved color fill in the vessels or in the heart chambers so temporal compounding improves our spatial resolution and our contrast resolution so remember that spatial compounding averaged images from different angles or temporal compounding is going to use images taken from the same angles but over time and to improve the image then it layers those same angled images upon one another to create a higher quality picture but it still requires the frames to be created and then averaged together so essentially again we are creating one frame from many pulses because we need more frames to create it and therefore temporal compounding can reduce your temporal resolution so again another graphical representation of temporal compounding remember in temporal compounding the images are taken all from the same angle it's just over time we are layering those pictures together so the first frame is created another frame is created and then the machine is going to lay those pictures on top of one another so we can get a nice averaging get rid of the noise that we don't need and really pull the signal out from the echoes that are coming back another frame is created and then it's layered on top of everything another frame is created and depending on how you have your persistence set up it might drop the oldest image and then layer the newest on top again a frame is created drop seal this image and then layers the new one on top so we're always creating images from multiple frames prior to the most recent one so here i have two cine of persistence this first one does not have persistence on so this is just gathering one frame and displaying it with the color doppler notice how the crowded itself is not filling very well we are getting color information but we're not really getting wall-to-wall fill compare that then to the bottom picture here where persistence is on it's actually kind of maxed out and so what we are seeing in this image are frames created over time being layered with one another so we're really getting a lot more information from that color doppler it's all getting layered on one another so we see a lot more color fill within the picture and that's because it's averaging those frames together showing us what the true signal is versus just one moment in time the last compounding technique then is frequency compounding and this is going to work a little bit differently than the other two types of compounding but we're going to get similar results and that it reduces noise and improves the signal frequency compounding is also known as frequency fusion now spatial and temporal compounding acquired separate frames and average them together frequency compounding is going to process different frequencies all at once instead of sequentially so if we look at our picture down here remember with spatial and temporal the machine would create a frame create a frame create a frame average them all together and then finally make that final frame with frequency compounding a five megahertz three megahertz and one megahertz wave are all emitted from the transducer and then the machine processes a five megahertz echo a three megahertz echo and a one megahertz echo all at the same time and then it can average them together and the reason i can do that is because remember the machine when it sends out its normal pulse has a bandwidth to it so it can listen for all sorts of different frequencies all at the same time process them and average them together now with the multiple frequencies we know that higher frequencies are going to attenuate as they travel deeper into the body so our five megahertz transducer is not going to image as far as the three and which is not going to image as far as the one but we still end up getting a really nice image especially in our near fields because we are able to layer all three of those frequency images on top of one another so the key part with frequency compounding is that it does improve spatial and contrast resolution that is because it is sending out multiple frequencies at once and processing images from those multiple frequencies all at once so same anatomy same time and because we are not sequentially adding frames on top of one another and because it's not adding more pulses to create one frame frequency compounding does not degrade our temporal resolution because it's all occurring at the same time so moving out of our compounding techniques i do want to bring up frequency tuning because i don't want this confused with frequency compounding the frequency tuning is still going to use that bandwidth that the transducer is capable of creating but instead of averaging three full frames together the frequency tuning is going to use the different frequencies to create layers in one image so those high frequencies are used only to create the upper portion of the field where the low frequencies are only used to create the far field and then we kind of have those middle frequencies for the middle portions of the image now because this is not an averaging or compounding technique we don't necessarily see that the signal-to-noise ratio is improved but we do see is that the lateral and axial resolutions are improved especially in the near and mid fields because we're using higher frequencies to create those parts of the picture it's important to note up to this point we've been talking about a lot of imaging features that take place in the image processor frequency tuning happens to be a beam former feature so if we look at our picture here again we are sending out that short little pulse that's going to have the large bandwidth multiple frequencies within it the machine then is going to listen for those frequencies coming back using only the high frequencies to create the image in the near field middle frequencies for the middle of the picture and then low frequencies to create the far field of the image another tool that occurs in the beam farmer is coded excitation so when we talked about axial resolution we learned that a short pulse is best right because axial resolution is the spatial pulse length divided by two well coded excitation is actually going to change that premise up a little bit coded excitation involves sending out a really long pulse that has little codes within it and each of those little coded parts is typically a very short pulse and then as the echoes come back from this long pulse the machine can kind of match up those little bits of pulse with one another and then kind of figure out how to place them and how to make a really nice picture from them so even though the polish itself is really long it is made up of those really short coated pieces and because of that we get an improved image without having to send out multiple pulses so in this example here this might be what a coated pulse looks like you can see that it is a very long pulse but here this part might be really good for the near field this is a lower frequency part of the pulse so that might be better for the far field and then we have these like little short guys in here and then with multiple amplitudes like there's just a whole bunch of stuff that goes into these coated excitated pulses lots of math goes into it then when they all come back to kind of figure out where all of these codes need to match up for but we get this down one scan line instead of a bunch of pulses to make one scan line so it actually is going to improve quite a few things in fact it actually has five benefits to it so the five benefits and you should know these four coded excitation most importantly is going to improve our axial resolution which again i know sounds really weird that we have this long pulse but remember it's the little pieces of this long pulse get kind of decoded and pulled out that's how we improve the axial resolution we're also going to get higher signal to noise ratio we're going to see improved spatial resolution improve contrast resolution we're actually going to get a little bit deeper penetration with the sound as well this is typically just a built-in feature of our newer machines not something that you would turn on or turn off as a sonographer it is included to optimize our imaging equipment next up then we have edge enhancement edge enhancement is going to make the picture look a lot sharper this is going to be a pre-processing function now we're back in the image processor so the machine is going to recognize where there are interfaces and between those interfaces it's going to create really a subtle bright and dark highlight on either side of a boundary because edge enhancement is improving the way that we can see boundaries then edge enhancement is going to improve our contrast resolution in this example here we have a very smooth looking image of a plane engine with the contrast if you look very carefully anywhere that there is an interface there's a kind of white or a highlight and then a low light on the other side and because of that then what we end up getting appear to be very very sharp edges so edge enhancement can improve the visualization of those borders because the machine recognizes where boundaries are and aims to enhance them getting into some of more of our contemporary features that we see on ultrasound machines we're going to start with elastography now lassography is a very helpful method of imaging that assesses the stiffness of tissue for many practitioners usually touching the patient to assess for masses or firm areas is really going to be important in the diagnostic process and this is definitely the case if we're talking about like breast lesions or thyroids because what we find is that benign masses tend to be kind of squishy and they kind of move around where cancers are more likely to be very firm and kind of fixed in place we also see that elastography is actually really helpful in determining the extent of fibrosis in the liver as the liver becomes more fibrous it becomes more stiff and we can measure that change in stiffness so essentially elastography can provide more information about the true stiffness of the tissue through what we call ultrasound palpation there are two different types of lastography the first type is strain elastography which you are seeing in this video here and this requires a sonographer to physically apply some pressure onto the body the machine then calculates how that tissue reacts to that pressure and then can provide a qualitative result that tells us is an area squishy or is it on the harder side so in this example here we can see that the transducer is being pushed which is why the anatomy shape and position is changing and we can see that our elastography map is being overlaid according to our map here anything that is blue is very soft or squishy if we had any reds in there those would be hard structures so this area here appears to be breast tissue as the sonographer pushes down on it we are seeing everything squished nicely suggesting that there is nothing firm or more likely to be a cancer located within this tissue the other type of elastography is called shear wave elastography now shear waves are the echoes that are going to move off to the sides in the tissue instead of those that are redirected back to the transducer the speed of the shear waves is measured by the machine and then a quantitative value is measured giving a number typically in kilopascals so remember that the propagation speed increases as stiffness increases so shear waves that move faster are considered to be in tissue that is stiffer so in this example here we are looking at the liver this little box here is our shear wave region of interest so the sonographer places this in usually hit a button and the machine is actually going to send out a pretty strong pulsed wave when it does that the pulse is sent in hits the soft tissue some echoes are returned but what we're going to get are those side directed waves and those are the shear waves the machine is going to measure how quickly these shear waves are moving and based on their speed we can then calculate the stiffness of the tissue so in this example here this liver came up at 5.6 kilopascals that is on the normal side of things typically around 20 is a very very severe case of fibrosis or stiffness in the liver so 5.6 is on the more normal side very similar to elastography we have something called cardiac strain imaging so elastography required outside force like pushing or using those shear waves to qualify the stiffness of the tissue but since the heart is made of muscle and its responses to electrical impulses basically make it its own strain crater so the machine can measure the stiffness of the heart muscle as they contract and relax something called the strain rate is going to show how effective the myocardium is at contracting so there are two different methods of cardiac strain imaging that can be achieved first one is through speckle tracing where the machine is going to watch a very certain area of the myocardium and it's tracked for movement or we can use something called tissue doppler in which colors are assigned to the tissue and the different colors mean different things the two methods essentially then are really describing the deformation of the cardiac wall or chamber from a relaxed to a contracted state so the image here we can see different views on the heart and then we actually have the strain rate posted here so the strain rate is looking at the different segments of the heart seeing are they kind of congruent with one another is there one area that like really stands out that might be an area of myocardial infarction or are they all kind of moving at the same rate relaxing at the same rate so it's really checking to see how much change in motion there is in the wall and to what degree and are the segments kind of operating in a similar pattern we've already talked a little bit about 3d imaging and 3d rendering but we do consider this a contemporary feature on many machines 3d rendering does require the machine to acquire ultrasound information in the three different planes after the acquisition of the data the information is saved and then can be manipulated to create the 3d image so because we are working with 2d saved data that makes this a post processing function so remember we are taking images in three different planes so that's either going to be manually sweeping through so we can get all three planes or newer transducers can image in all three planes all at once and then we kind of put this overlay on the top of it giving it a little bit more of a realistic tissue like appearance to it and then we call these our 3d rendered images before i leave i do just have a few final thoughts on all of those image processing techniques that we've talked about there were a couple from the list that we did not get to that was dynamic range harmonics and contrast imaging that is because they each have their own units that are coming up these techniques are used very often in ultrasound and because they are so prevalent in our imaging they do warrant having their own units each so shorter units but uh they'll go a little bit more detailed than what would have been appropriate for this section otherwise all the other imaging processing techniques and the contemporary features that we've talked about i'll typically have a very explicit purpose for existing for all of our compounding techniques the whole idea was to make better pictures so the signal-to-noise ratio becomes improved we get rid of that extra noise we're improving the signal some of them were clearly focused on improving the contrast resolution how well can we see borders and the pixels and everything else that's made into the picture or spatial resolution was the focus does it change the detail that we can see in the picture so really focus on how these tools improve our pictures what was the purpose that they are being used and then after that you should know the definitions of all of them kind of know the basics of what's happening for each technique and then know to if it was a pre or post processing function and that brings us to the end so make sure to go through your very brief activity that is in the workbook and then there are a handful of questions that you can go over as well in your nerd check