@article{oai:mie-u.repo.nii.ac.jp:00006447,
 author = {Kodama, Dai and Yamakawa, Ai and Tsuruoka, Shinji and Kawanaka, Hiroharu and Takase, Haruhiko and Uji, Yukitaka and Matsubara, Hisashi and Okuyama, Fumio},
 issue = {2},
 journal = {Proceedings of the Second International Workshop on Regional Innovation Studies :  (IWRIS2010)},
 month = {Oct},
 note = {application/pdf, In ophthalmology, optical coherence tomography
(OCT) is rapidly becoming popular to diagnose retinal diseases.
However, the quantitative evaluation of retinal diseases has not
been established for OCT image. Some clinical doctors desire a
computer-aided diagnosis system to evaluate the size and the
degree of disease quantitatively. In previous researches, the
size of the retinal diseases is measured as abnormal parts of
small regions in the number of layer boundaries, which is
estimated by analysis method on a gray level profile for an
OCT image. However, in an abnormal part, the difference of
the number of layer boundaries is small between abnormal
parts and normal parts, and the previous method can’t detect
the size of the abnormal part. In this research, we propose a
new method to measure the size of abnormal parts using correlation
coefficient in gray level distribution for an OCT image.
In the gray level distributions of the OCT image, the correlation
coefficient is large in normal parts, and the coefficient is
small between normal regions and abnormal parts. Therefore,
our system can detect the position of borders between abnormal
parts and normal parts using the distribution of correlation
coefficient. We apply the proposed method to some retinal
disease images. For an OCT image, we obtained the overlap
rate 92.3[%] between the identified part by the proposed method
and the clinical doctor for the abnormal part. The overlap
rate is improved for 21 OCT images among 25 OCT images,
and the improved rate in the proposed method is 84[%]
compared with the previous method},
 pages = {79--82},
 title = {A Proposal of Measuring Method for the Size of Abnormal Part Using Correlation Coefficient on Intensity Distribution from Optical Coherence Tomography Images},
 year = {2011}
}