Fujitsu Develops AI-Based Technology to Retrieve Similar Disease Cases in CT Inspections
2017年6月26日 - 09:08AM
JCN Newswire (英)
Fujitsu Laboratories Ltd. today announced development of a
technology to retrieve similar disease cases from a computed
tomography (CT) database of previously taken images. The
technology, jointly developed with Fujitsu R&D Center Co.,
Ltd., works by retrieving similar cases of abnormal shadows
expanding in a three-dimensional manner.
Technologies already exist to retrieve similar cases based on CT
images for such diseases as early-stage lung cancer, in which
abnormal shadows are concentrated in one place. For diffuse lung
diseases like pneumonia, however, in which abnormal shadows are
spread throughout the organ in all directions, it has been
necessary for doctors to reconfirm three-dimensional similarities,
increasing the time needed to reach a conclusion.
Now Fujitsu Laboratories has developed an AI-based technology that
can accurately retrieve similar cases in which abnormal shadows
have spread in three dimensions. The technology automatically
separates the complex interior of the organ into areas through
image analysis, and uses machine learning to recognize abnormal
shadow candidates in each area. By dividing up the organ spatially
into periphery, core, top, bottom, left and right, and focusing on
the spread of the abnormal shadows in each area, it becomes
possible to view things in the same way doctors do when determining
similarities for diagnosis. In joint research with Professor Kazuo
Awai of the Department of Diagnostic Radiology, Institute and
Graduate School of Biomedical Sciences, Hiroshima University, this
technology was tested using real-world data, and the result was an
accuracy rate of 85% in the top five retrievals among correct
answers predetermined by doctors. This technology is expected to
lead to increased efficiency in diagnostic tasks for doctors, and
could reduce the time required to identify the correct diagnosis
for cases in which identification previously took a great deal of
time.
Going forward, Fujitsu Laboratories will conduct numerous field
trials using CT images for a variety of cases, while additionally
aiming to contribute to the increased efficiency of medical care by
deploying this technology with related solutions from Fujitsu
Limited.
Details of this technology will be announced at the Pattern
Recognition and Media Understanding (PRMU) conference to be held by
the Institute of Electronics, Information and Communication
Engineers at Tohoku University (Sendai, Miyagi prefecture) on June
22-23.
Development Background
The number of images produced in imaging inspections for detecting
diseases using CTs is increasing with the growing sophistication of
imaging equipment, making an ever-increasing workload for doctors.
This is particularly true because a significant percentage of the
number of chest CT inspections consist of those for a group of
diseases called diffuse lung diseases, in which abnormal shadows
spread across the whole of the lungs, including numerous diseases
such as interstitial pneumonia and emphysema. The interpretation
and diagnosis based on these CT images requires a great deal of
knowledge and experience, as well as a significant amount of time,
and has become an issue for doctors. This has created demand for a
technology that retrieves similar cases from the past with
diagnosis and treatment information that can serve as a reference
in the doctor's decision making, in order to improve the efficiency
of interpretation and diagnosis.
Issues
There are existing technologies that allow a doctor to specify an
area of focus in a certain slice image, and retrieve other patients
with similar slice images. These technologies have been useful when
the abnormal shadows are concentrated in one place, as with
early-stage lung cancer. In the case of diffuse lung diseases,
however, in which the abnormal shadows are spread in all directions
across the organ as a whole, retrievals employing this method could
find cases that while appearing similar in certain slice images,
would not necessarily look the same in three dimensions. To rule
out such cases, doctors had to re-check the results to ensure their
similarity in three dimensions, taking up a great deal of time
(Figure 1).
http://www.acnnewswire.com/topimg/Low_FujitsuAICTFig1.jpg
Figure 1: Existing retrievals for similar cases
About the Newly Developed Technology
Fujitsu Laboratories has focused on the way that doctors, when
determining the similarity of images, divide the organ into
three-dimensional areas, such as periphery, core, top, bottom, left
and right, and how doctors look at the spread of abnormal shadows
in each area. To be able to look at this problem in the same way as
doctors, Fujitsu Laboratories developed AI-based technology that
accurately retrieves CT images with a similar spread of abnormal
shadows in three dimensions using image analysis to automatically
separate the areas of the interior of the organ, where boundaries
can be difficult to visually determine, and using machine learning
to recognize abnormal shadow candidates in each area. As part of
this, technology to recognize abnormal shadow candidates was
jointly developed with Fujitsu R&D Center, Co., Ltd.
http://www.acnnewswire.com/topimg/Low_FujitsuAICTFig2.jpg
Figure 2: How a doctor analyzes images
With this technology, abnormal shadow candidates are first
recognized from CT images using machine learning (Figure 3(a)).
Next, by estimating the boundaries of the core and the periphery
based on the relatively clear parts of the CT image in succession,
the technology divides the lungs into core and peripheral areas
(Figure 3(b)).
Next, following the axis of the body up and down, the technology
creates histograms (Figure 3(c)) of the number of abnormal shadow
candidates located in the core and peripheral areas, then looks at
the three-dimensional spread of abnormal shadows to retrieve
similar cases.
http://www.acnnewswire.com/topimg/Low_FujitsuAICTFig3.jpg
Figure 3: Newly developed technology to retrieve similar cases
Effects
In joint research with Professor Kazuo Awai of the Department of
Diagnostic Radiology, Institute and Graduate School of Biomedical
Sciences, Hiroshima University, the results of evaluation
experiments demonstrated that when this technology was tested using
CT images of diffuse lung diseases, it was able to retrieve similar
cases with an accuracy of about 85% in the top five retrievals
among correct answers determined by doctors. With this technology,
it is expected that diagnostic tasks that doctors had previously
performed by hand, such as searching for similar cases from
literature, can become more efficient, with the possibility of
shortening the diagnostic time required for a doctor to evaluate a
case to as great as one-sixth of previous levels, for cases where
evaluation took a great deal of time.
Future Plans
This technology could be applied not only to the diagnosis of
diffuse lung diseases, but also to other imaging diagnostic
techniques, including head CTs and stomach CTs, as well as MRIs
(Magnetic Resonance Imaging) and ultrasounds. Fujitsu Laboratories
will conduct numerous field trials using CT inspections for a
variety of cases, while additionally aiming to contribute to the
increased efficiency of medical care by deploying this technology
with related solutions from Fujitsu Limited.
Comment from Professor Kazuo Awai, Department of Diagnostic
Radiology, Institute and Graduate School of Biomedical Sciences,
Hiroshima University
The fact that we have been able to demonstrate the possibility of
retrieving CT images where abnormal shadows have similar natures
and three-dimensional distribution has important medical
implications. Moving forward, this technology has the potential to
provide doctors with clinically useful information by retrieving
similar CT images from cases that were difficult to diagnose and
treat, and we can anticipate that this will improve the accuracy
and efficiency of medical care. By grouping morphologically similar
images, and investigating whether there are any common genetic
abnormalities within these groups, the technology may present new
ways of thinking about diseases and offers the possibility of
numerous clinical applications-it's a technology that we have great
expectations for in the future.
About Fujitsu Laboratories
Founded in 1968 as a wholly owned subsidiary of Fujitsu Limited,
Fujitsu Laboratories Ltd. is one of the premier research centers in
the world. With a global network of laboratories in Japan, China,
the United States and Europe, the organization conducts a wide
range of basic and applied research in the areas of Next-generation
Services, Computer Servers, Networks, Electronic Devices and
Advanced Materials. For more information, please see:
http://www.fujitsu.com/jp/group/labs/en/.
About Fujitsu Ltd
Fujitsu is the leading Japanese information and communication
technology (ICT) company, offering a full range of technology
products, solutions, and services. Approximately 155,000 Fujitsu
people support customers in more than 100 countries. We use our
experience and the power of ICT to shape the future of society with
our customers. Fujitsu Limited (TSE:6702) reported consolidated
revenues of 4.5 trillion yen (US$40 billion) for the fiscal year
ended March 31, 2017. For more information, please see
http://www.fujitsu.com.
* Please see this press release, with images, at:
http://www.fujitsu.com/global/about/resources/news/press-releases/
Source: Fujitsu Ltd
Contact:
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