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find Author "ZHU Zhenyu" 2 results
  • Research on Method of Pancreaticoenterostomy

    Objective To investigate the new method of pancreaticoenterostomy and decrease the probability of complications like pancreatic fistula etc. Methods By using the absorbable bandage and ear-brain glue, modified sutureless pancreaticoenteromy was made in 10 swines. Experimental data includes: routine analysis of blood, levels of amylase in blood and abdominal drainage and lipase in blood and abdominal drainage. The tissues in anastomosis were taken for pathology examination in 1 month after operation. Results The average operative time was (35±10) min.Nine of ten animals had no pancreatic fistula and survived. The levels of amylase and lipase in abdominal drainage were both normal. One swine had a evident abdominal distensile on 2 days after operation, the level of amylase was 10 000u/L,then died on 10 days after operation. Pancreatic fistula and infection were found because of the loss of stent in pancreatic duct. Conclusions Comparison with traditional operation, the modified sutureless pancreaticoenteromy can also control the probability of pancreatic fistula. And this method can be hoped to be one of the routine operations of pancreaticoenterostomy because of its simplicity and practicality.

    Release date:2016-09-08 10:37 Export PDF Favorites Scan
  • A multi-label fusion based level set method for multiple sclerosis lesion segmentation

    A multi-label based level set model for multiple sclerosis lesion segmentation is proposed based on the shape, position and other information of lesions from magnetic resonance image. First, fuzzy c-means model is applied to extract the initial lesion region. Second, an intensity prior information term and a label fusion term are constructed using intensity information of the initial lesion region, the above two terms are integrated into a region-based level set model. The final lesion segmentation is achieved by evolving the level set contour. The experimental results show that the proposed method can accurately and robustly extract brain lesions from magnetic resonance images. The proposed method helps to reduce the work of radiologists significantly, which is useful in clinical application.

    Release date:2019-06-17 04:41 Export PDF Favorites Scan
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