YORKTOWN HEIGHTS, N.Y.,
Dec. 17, 2014 /PRNewswire/ -- IBM (NYSE: IBM) announced today
a collaboration with Memorial Sloan Kettering to research the
application of cognitive computing to analyze dermatological images
of skin lesions with the goal of assisting clinicians in the
identification of various cancerous disease states. The technology,
which learns by identifying specific patterns in medical images,
has the potential to increase the number of cases detected and help
clinicians make earlier diagnoses.
Despite efforts to address risk factors, skin cancer is still
the most commonly diagnosed cancer in the United States with nearly
5 million people treated for the disease every year, at an
estimated cost of $8.1 billion. Melanoma, the most deadly form of
skin cancer, causes nearly 9,000 deaths each year.
The automated analysis of skin imaging is one area of research
that is currently being investigated by IBM Research, in
conjunction with a larger international effort being led by
Memorial Sloan Kettering.
Dr. Allan Halpern, Chief of
Dermatology Service at Memorial Sloan Kettering, said, "Skin cancer
is a major public health problem. Treatment options exist, with the
best outcomes attained through early detection. However, accurately
distinguishing the earliest cancers from concerning benign lesions
can be very challenging even for dermatologists, so having the aid
of analytics that can recognize medical images and detect small
variations over time could vastly improve patient prognoses."
Currently, diagnostic accuracy varies widely across clinicians,
institutions, and the availability of expertise. Even when the
appropriate expertise is available, diagnostic accuracy is
estimated between 75-84%. Critical evidence in these
images is often subtle, requiring experience and careful
measurement to recognize. Using cognitive visual capabilities being
developed at IBM, computers can be trained to identify specific
patterns in images by gaining experience and knowledge through
analysis of large collections of educational research data, and
performing finely detailed measurements that would otherwise be too
large and laborious for a doctor to perform. Such examples of
finely detailed measurements include the objective quantification
of visual features, such as color distributions, texture patterns,
shape, and edge information. Algorithms could also measure temporal
morphological progression of lesions (such as aggressive growth
over a short span of time), or deviations from what is considered
normal for a single patient or sub-population. Combinations
of these types of analyses could identify for the clinicians,
nuanced patterns in dermatological images that may signify
disease.
Preliminary experiments have been performed using a
controlled research dataset of dermoscopy images (a
specialized imaging technique used by dermatologists) containing
over 3,000 cases of melanoma, atypical lesions, and benign lesions.
In this dataset, the technology developed by IBM recognized
diseased states with a performance of 97% sensitivity, and 95%
specificity.
"Given the incredibly high incidence and mortality rate of skin
cancer, there's a real opportunity to have a clear and significant
impact on the health and longevity of individuals on a global
scale. At IBM, we are uniquely equipped to help tackle this problem
with our expertise in cognitive computing, including machine
learning and visual analytics," said Dr. Noel Codella, IBM Research Staff Member, and IBM
Technical Coordinator for the collaboration.
IBM has historically shown leadership and expertise in the
development of advanced techniques in visual analytics. Key
technologies previously developed that are relevant to the ongoing
work include the IBM Multimedia and Analytics System, an award
winning visual machine learning architecture, Medical Sieve, a
system for the analysis of medical images, and Intelligent Video
Analytics (IVA), a visual recognition and search system.
About IBM:
For more information visit
www.research.ibm.com
Contact:
Fiona Doherty
IBM Research
fhdohert@us.ibm.com
914-945-2319
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SOURCE IBM