Quantitative evaluation of diagnostic information around the contours in ultrasound images.
OBJECTIVE
To develop a new contour extraction method for identifying abnormal tissue.


METHODS
We combined two techniques: logarithmic K distribution of a scattering model (method 1) and regional discrimination using the characteristics of local ultrasound images (method 2) into an integrated method (method 3) that provides accurate contours, which are essential for quantitizing border information.


RESULTS
The diagnostic tissue information around the border of an image can be characterized by its shape and texture statistics. The degrees of circularity and irregularity and the depth-width ratio were calculated for the extracted contours of breast tumors. In addition, gradients, separability, and variance between the two regions along the contour and the area and variance of the internal echoes, were calculated as indices of diagnostic criteria of breast tumors. The quantitized indices were able to discriminate among cysts, fibroadenomas, and cancer.


CONCLUSIONS
In many ultrasound images of breast tumors, the combined techniques, the variance ratio of the logarithmic K distribution to the logarithmic Rayleigh distribution and the multilevel technique with local image information can effectively extract abnormal tissue contours.
Tokyo Denki University, Graduate School of Sciences and Engineering, Hatoyama-machi, Hiki, Saitama, 350-0394, Japan. ito@re.ccs.dendai.ac.jp.|Tokyo University of Agriculture and Technology, Tokyo, Japan. ito@re.ccs.dendai.ac.jp.
Masayasu
M
Ito
Tokyo University of Agriculture and Technology, Tokyo, Japan.
Tomoaki
T
Chono
Tokyo University of Agriculture and Technology, Tokyo, Japan.
Megumu
M
Sekiguchi
University of Tsukuba, Graduate School of Systems and Information Engineering, Tsukuba, Japan.
Tsuyoshi
T
Shiina
The Third Department of Internal Medicine, Kyorin University School of Medicine, Tokyo, Japan.
Hideaki
H
Mori
University of Tsukuba, Graduate School of Comprehensive Human Science, Tsukuba, Japan.
Eriko
E
Tohno
K distributions; Rayleigh distributions; contour; quantitative diagnostic information; ultrasonography