A Study For Semi-automatic Diagnosis Support
Of Strokes From 2D MRI/FLAIR Sequences
Author(s)
C. Doi, A. Doi, T. Obara, T. Inoue, M. Sasaki & A. Ogawa
Abstract
The MRI/FLAIR sequence is being used for the diagnosis of strokes. The
bleeding area shows a high intensity in most cases. However, a doctor must
check each image which can take a lot of time. We found that in this process a
skilled doctor typically checks the gap area (internal cavity) of the brain to give a
diagnosis. This fact is confirmed by a questionnaire of several neuro surgeons. In
order to extract the gap area, we utilize a region growing method and a 2D
deformable model. We also improve the preciseness by eliminating high
intensity areas near the bulb of the brain. Finally, we calculate the degree of riskfactor
by counting pixels with high intensity in the gap area. From our
experience, we found that the histogram of strokes had a similar pattern, and it
could be used for diagnosis of strokes. Finally, we visualize the distribution of
the bleeding area of the stroke, and evaluate the results in several ways.
Keywords: diagnosis support, stroke, MRI, region growing method, image
processing.
1 Introduction
Every year a very large number of people suffer from strokes. It is necessary for
stroke victims to take an urgent treatment, because the death rate is very high,
and the after-effects, such as paralysis of one side of the body, are common. Both
CT and MRI are being used for the diagnosis of strokes. A bleeding area in CT
and MRI shows high intensity in most cases. However, small cerebral
hemorrhage often leads to misdiagnosis, since the area of bleeding is too small,
and the intensity in the area is low. This often happens in the emergency hospital
where a neuro surgeon is not present. Moreover, a doctor also must check each
Keywords
diagnosis support, stroke, MRI, region growing method, image
processing.
Related Book
Other papers in this volume
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