Google-like process for mammogram images speeds up computer's second opinions

Jul 26, 2006

To help computers provide faster "second opinions" on mammogram images showing suspicious-looking breast masses, medical physicists at Duke University are employing a Google-like approach that retrieves useful information from an existing mammogram database within three seconds.

Rather than comparing the mammogram image in question to every image of breast cancer in a computer database, the new approach compares the mammogram in question to selected images that are most highly ranked for their information content. This is analogous to how a Google search first returns a list of only those websites that it determines to have the most important and useful information on the words entered in the search.

In a pilot study that will be presented in August at the 48th Annual Meeting of the American Association of Physicists in Medicine in Orlando, the approach enabled computers to maintain their high level of accuracy while performing faster analysis. Such speed and efficiency will be important as such image databases rapidly grow larger and more complex.

Knowledge-based computer-assisted detection (CAD) systems compare mammogram images to those of known cases of breast cancer in order to aid radiologists in their diagnosis. However, as clinical image libraries grow rapidly in mammography practice, knowledge-based CAD systems get slower and less efficient.

In efforts to prevent such systems from bogging down, Duke's Georgia D. Tourassi, Ph.D. will present a Knowledge-Based Computer Assisted Detection (KB-CAD) system that analyzes breast masses using the principles of information theory.

When a new, unknown case is presented for analysis, the KB-CAD system compares the case to mammography images in the database. It retrieves cases that are similar, those that share certain visual features and properties. If the unknown case is similar enough to a known case of breast cancer, then this would suggest the presence of cancer.

Although diagnostically accurate, this practice becomes inefficient as the image database increases in size. Therefore, the researchers incorporate an additional approach.

Instead of comparing the new unknown case with all mammography images stored in the knowledge database, the researchers restrict the analysis to the stored cases that are most informative. The selection of the most informative cases is done using an image indexing strategy based on the concept of "image entropy." Image entropy represents a measure of the disorder or complexity in the image. An image that is all black or white has zero entropy. An image of a checkerboard has low entropy--it consists of an equal number of light and dark pixels. Complex images with more uniform distributions of many pixel intensity levels have higher entropy and are considered more informative in the context of the Duke system.

Normal breast tissue "can be as complex as a tumor," Tourassi says. "This is precisely the reason mammographic diagnosis is such a challenging task. Our database inlcudes normal cases as well in the decision-making process."

In the recent pilot study, the Duke researchers applied their technique to a database of 2,300 mammography images. With entropy indexing, the researchers compared a sample image to the top 600 most informative, cutting down their CAD system's processing time by one-fourth, to less than 3 seconds per query. The researchers expect to launch a larger study in a year to evaluate the clinical impact of this new approach.

Source: American Institute of Physics

Explore further: Black holes do not exist where space and time do not exist, says new theory

add to favorites email to friend print save as pdf

Related Stories

Google to update translation app for phones

Jan 12, 2015

Quentin Hardy of The New York Times said it well: The tech industry is trying "to topple the Tower of Babel." He said that 80 to 90 percent of the web is in just 10 languages. Google, for one, has made i ...

A new, public view of the sky

Jan 07, 2015

For the first time, scientists and the public are beginning to see the large-scale structure of the universe, thanks to the Sloan Digital Sky Survey. UA scientists provide scientific expertise and crucial ...

Health checks will be seated by Sharp

Dec 08, 2014

(Phys.org) —Sharp unveiled a news-making prototype of a sensor earlier this month at Semicon Japan 2014, which took place from Dec 3 to 5. As its title suggests, Sharp's "Blood Vessel Aging Degree Sensor" ...

Knightscope K5 on security patrol roams campus

Nov 24, 2014

A Mountain View, California-based company called Knightscope designs and builds 5-feet, 300-pound security guards called K5, but anyone scanning last week's headlines has already heard about them, with the ...

Recommended for you

Seeking cracks in the Standard Model

15 hours ago

In particle physics, it's our business to understand structure. I work on the Large Hadron Collider (LHC) and this machine lets us see and study the smallest structure of all; unimaginably tiny fundamental partic ...

Building the next generation of efficient computers

Jan 29, 2015

UConn researcher Bryan Huey has uncovered new information about the kinetic properties of multiferroic materials that could be a key breakthrough for scientists looking to create a new generation of low-energy, ...

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.