Chien-Cheng Lee, Sz-Han Chen, Hong-Ming Tsai, Pau-Choo Chung, and Yu-Chun Chiang

Department of Communications Engineering, Yuan Ze University Chungli, Taoyuan 320,

Taiwan

IntroductionThe accurate decision rate estimated by

using only simple visual interpretation of liver diseases is around 72%.

In this papperThe diagnosis scheme includes two steps:

features extraction classification

Three kinds of liver diseases are identified: cyst, cavernous hepatomaHemangioma

Features extractionGabor filters have the ability to model the

frequency and orientation sensitivity characteristic of the human visual system.

The features are optimal in the sense of minimizing the joint two-dimensional uncertainty in space and frequency.

2D Gabor filter

Where,

2

22

2 2

yxexp

2

1y , xg

‧ 1j

Frequency: ψOrientation: θBandwidth: σ

θθψ‧θψ sinycosx2jexp y , xgy , xG , ,

2D Gabor filter2-D convolution with image:

),(),(, ,, yxjGyxGyxGWhere IR θψ

yxG R , = θθψ‧ sinycosx2 cos y , xg

yxG I , = θθψ‧ sinycosx2sin y , xg

j i

, , j,iG jy,ixfy,x G θψ‧

The convolution is implemented using the mask of M×M sizes, which M is preferred to be an odd number.

2D Gabor filterEnergy

Minimum Energy

22 ,,,,,,,,, θψθψ yxGyxGyxE IR

22 ,,,,,,,,, θψθψ yxGyxGyxEMin IR

Supervised diseases classificationSupport Vector Machines

Train linear machines with marginsPreprocessing the data to represent patterns in

a high dimension with an appropriate nonlinear mapping Data from two categories can be linearly separable

Find the separating plane with largest margin The larger the margin, the better generalization of

the classifier

SVM

SVMFor linearly separable data set, the optimal

separating hyper-planes can be defined as follows:

where is a subset of the training patterns calledSupport Vectors (SVs).

SVMThe coefficients and b are obtained by

solving the optimization problem:

The parameter C is a regularization parameter selected by the user. C corresponds to assigning a payment to the training errors.

ExperimentThe images is 512 × 512 with contrast media

injection and the graylevel is stored at 12 bits per pixel, include76 liver cysts30 hepatomas 40 cavernous hemangiomas

Result