Name: 【TED】安德斯-英納曼：醫療數據爆炸的可視化（Anders Ynnerman: Visualizing the medical data explosion）。 (【TED】Anders Ynnerman: Visualizing the medical data explosion (Anders Ynnerman: Visualizing the medical data explosion))
Uploaded: 2021-01-14T07:26:46.000Z
Duration: 17 min 7 s

I will start by posing a little bit of a challenge:

首先我先向大家介紹一個亟需解決的難題

that are rotating very fast around the human body.

它使用X線管發出X線束對患者進行掃描,

It takes about 30 seconds to go through the whole machine

同時這些X線管會圍繞患者高速旋轉.

and is generating enormous amounts of information

but as I said, it's also a challenge for us.

And the challenge is really found in this picture here.

但正如之前所說,它也為我們帶來了一個問題.

從這張圖片大家可以看到這個問題.

Let's go back a few years in time and see what happened back then.

醫生們用這些機器對患者進行人體掃描.

And I've taken the liberty, just for clarity,

That would correspond to about 50 megabytes of data,

我把這圖像轉換成等量的數據切片.

這些圖像大約相當於50MB的數據,

when you think about the data we can handle today

如果和現在我們每天打交道的信息量相比

it's about one meter of phone books in the pile.

如果拿電話簿的信息量做比的話,

and that would correspond to about 20 gigabytes of data,

一位患者的人體掃描可以得到24,000張影像.

and the pile would then be 200 meters of phone books.

a technology trend that's happening right now

我們可以看到,它已經開始了----

is that we're starting to look at time-resolved situations as well.

So we're getting the dynamics out of the body as well.

我們也需要得到書面化的診斷結果.

that we will be collecting data during five seconds,

and that would correspond to one terabyte of data --

我們收集到了掃描5秒鐘所得數據,

這還只是掃描一個病患所得數據集.

So this is really the enormous challenge that we have.

這也正是我們需要處理的數據量

And already today -- this is 25,000 images.

現在正是這個問題. 這裡有25,000張影像.

they would go like this, "25,0000, okay, okay.

放到現在,他們要放25,000張圖像上去,

到時候他們就要像這樣去看,”第25,000張,

They can't do that anymore. That's impossible.

So we have to do something that's a little bit more intelligent than doing this.

So what we do is that we put all these slices together.

所以我們要想一些更聰明的辦法.

Imagine that you slice your body in all these directions,

and then you try to put the slices back together again

我們先把自己沿這些各種方向切成數據片,

into a pile of data, into a block of data.

然後把這些切片再重新放回到一起,

這樣一堆數據就成了一個數據塊

So this gigabyte or terabyte of data, we're putting it into this block.

把這許多GB、TB的數據合成一個數據塊

that's been absorbed in each point in the human body.

So what we need to do is to figure out a way

of looking at the things we do want to look at

接下來我們要做的就是想個辦法

and make things transparent that we don't want to look at.

只顯示我們想看到那部分的數據,

This is a huge challenge for us to do that.

Using computers, even though they're getting faster and better all the time,

it's a challenge to deal with gigabytes of data,

雖然現在電腦運行已越來越快且穩定

並提取出所需信息依然並不容易.

I want to look at the blood vessels. I want to look at the liver.

有時候要看一下血管,有時看肝臟,

So this is where this little dear comes into play.

behind the development of graphics-processing units.

As long as kids are playing computer games,

graphics is getting better and better and better.

So please go back home, tell your kids to play more games,

電腦圖像處理技術就會越來越好.

【TED】安德斯-英納曼：醫療數據爆炸的可視化（Anders Ynnerman: Visualizing the medical data explosion）。 (【TED】Anders Ynnerman: Visualizing the medical data explosion (Anders Ynnerman: Visualizing the medical data explosion))

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【TED】安德斯-英納曼：醫療數據爆炸的可視化（Anders Ynnerman: Visualizing the medical data explosion）。 (【TED】Anders Ynnerman: Visualizing the medical data explosion (Anders Ynnerman: Visualizing the medical data explosion))

relevant

situation

enormous

physical