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Regarding reconstruct algorithms, every image when it is

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reconstructed, it goes through different algorithms

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to generate the images.

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Prior to that, I also want to share one other concept called

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display field of view.

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So this is a scanner of a head CT, but this displayed into

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25-centimeter display field of view.

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Means the object is out, the scan is obtained, now we can express

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displaying in different size. If this is obtained at 25

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centimeter, the object displayed and the image looks like this.

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If it is a display set at 10 centimeter,

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only part of the image is displayed.

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So that is where it is,

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one of the trade-off is the display field of view can

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never exceed the scan field of view.

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Means you can't suddenly reconstruct image outside the scan field of view is

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what the take-home message.

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Among the reconstruction algorithm, this is one of the secrets of all

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the vendors, how they reconstruct the image.

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They use lot of the mathematical approximation and benefit to display the

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image very accurately.

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These things affect both the spatial and contrast resolution,

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which we're going to discuss later.

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And that is selected based on the clinical lead.

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Irrespective of the vendor, I like to categorize the reconstruct

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algorithm family into three different categories.

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The sharp reconstruct algorithms,

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soft reconstruct algorithms, and standard reconstruct algorithms.

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So now this is part of the secondary factor

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because once the image is obtained now, you can

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reconstruct using sharp algorithm to display very sharp

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object such as the lungs or the sharp or

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very fine structure or the soft.

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So the raw data is already obtained.

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Now we can fix it in different reconstruct algorithm and the standard algorithms.

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So what I want to show you here is like the family of

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smooth algorithms,

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medium algorithms, and sharp algorithms, and how

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them impact the image noise and the spatial

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resolution. If you just see the image noise, the

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image noise in the images reconstructed with the smooth algorithms are

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as the lowest image noise.

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The same data reconstructed with the sharp algorithm, the image noise is very

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high. However, in terms of spatial resolution,

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the spatial resolution is poor with the smooth algorithm, is

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very high with the sharp algorithm.

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So that's where the trade-off comes into picture.

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Here is a simulated images,

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very smooth algorithm, where the standard deviation is here,

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26.9, and here the standard deviation is

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107 standard deviation, and this is a very noisy,

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and this is using a ultra-sharp reconstruct algorithm.

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And the reconstruct interval also impacts how the images are

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displayed. This is a reconstruct interval of five millimeter, whereas a reconstruct

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of one millimeter is a finer thing.