Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.
A new solution to recover 6DoF (Degrees of Freedom) ego-motion is present. The problem is to estimate the ego-motion
information solely from dense optical flow (OF) field efficiently and robustly, free of Inertial Measurement Unit (IMU).
The algorithm is a hierarchical framework and in each level there exist three parts, which are the optical flow
Computation(OFC), the ego-motion estimation(EME) from two different models, and image warping(IW) according to
the EME for the next level. The numerical precision of the algorithm under noise was investigated in the paper. We also
compared its performance with Srinivasan's interpolation method and the 4DoF affine model on real aerial images. Our
method are more accurate under large displacements and can resist the impacts of the rotations around x and y axis in a
reasonable extent during computer navigation simulation.