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Cold is a factor affecting health in humans and animals. The liver, a major metabolic center, is highly susceptible to ambient air temperature. Recent studies have shown that endoplasmic reticulum (ER) stress is associated with the liver, and regulates the occurrence and development of liver injury and autophagy. However, the mechanism underlying the relationship between cold exposure and ER stress...
AFP-producing gastric carcinoma(APGC) are known to have a poorer prognosis and to show a higher incidence of liver metastasis than ordinary gastric carcinoma. Therefore, surgical resection, chemotherapy or radiotherapy is usually not satisfactory. In recent years, effects of arsenic trioxide (As2O3) on cell proliferation and induced apoptosis of solid tumors have been widely studied, while little...
The detection of region of interest (ROI) in medical images has played a very important role in computer aided diagnose. With respect to liver-focus pixels having weak textural and similar intensities with their neighborhood, a novel detection algorithm of abnormal regions in liver CT images has been proposed in this paper by visual attention model. Firstly, a set of statistical texture features for...
Liver segmentation from CT image is a difficult task due to abdomen apparatus complexity. Snakes, or active contours, are extensively used in medical image segmentation. The automatic generation of initial snake curves and improving snake performance in case of blur edges are still open challenges for liver segmentations. In this paper, texture classification and morphology filter are employed to...
Contour extraction of liver tissues in CT image is particularly challenging due to the anatomic complexity. An integrated model based statistical learning and active contour scheme - modified snake are presented in the paper to simplify the automatically liver contour extraction and then achieve refinements of liver boundary with accuracy. The proposed scheme consists of two sub-routines: initial...
Segmentation of liver tissues in CT image is particularly challenging due to the anatomic complexity. An integrated model based statistical learning and morphology operations are presented in the paper to simplify the liver segmentation procedure and achieve qualified results simultaneously. The proposed scheme consists of two subroutines: initial segmentation and refinement. The former estimates...
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