Tan Wenjun

An automatic partitioning method of CTA head-neck image

The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.

A novel registration method of brain PET images and Talairach atlas

In recent years, the PET as an important clinical examination imaging technology of radionuclide imaging has become the indispensable tool of for cancer and neurological diseases diagnosis. For the defect of poor resolution and brain structural features are not clear on PET image, it is difficult to select the points accurately when brain PET image register for the brain atlas. The CT image has good spatial resolution and high density resolution. So a novel registration algorithm of PET and standard brain atlas is presented in this paper by transforming PET-CT-atlas multimodality image based on marking the feature points on the CT images. Firstly, the brain tissue, the minimum oriented bounding box and the mid-sagital plane are extracted from brain CT images. Secondly, the brain cortical landmarks is manually marked from CT images and transformed into PET images with mutual information matrix of PET-CT images. Finally, the automatic registration of PET-Talairach atlas is realized with the spatial affine transformation matrix, which is calculated by using the brain cortical landmarks of PET image and Talairach atlas. The experimental results show that the method of multi modality registration of PET-CT-T atlas greatly reduces the error of manual intervention, and is good accuracy and lower time complexity.