RESUMEN
Objective:To investigate the current situation of damage compensation for subjects in drugs clinical trials.Methods: Retrospective analyzes was conducted on 70 drug clinical trail from January 2008 to December 2014 in our hospital , including protocols、informed consent and insurance .Results: It was written in most proto-cols that sponsor undertook damage compensation due to experimental drugs , however , lack of detailed rules .Dam-age compensation for subjects was missed in some informed consents .17 drugs clinical trials provided insurance , the rate of jointing insurance 24 .3%.In international trail , the rate of jointing insurance ( 100%) was higher than that in domestic trail (9.1%).As to domestic trail, the rate of jointing insurance increased gradually .There was no difference between insurance of different periods .In 17 insurance , 13 were clinical trial liability insurance , oth-ers were product and general liability insurance;5 provided insurance instruction , only insurance certificate or poli-cy in others;2 insurance applied foreign language .Conclusion:Through project access system , strengthening the ethical approval , strengthening quality management to prevent the damage occurred , participants damage happened after fully protect the health and rights and interests of the subjects , and actively promote clinical trial insurance to perfect our subjects′damage compensation mechanism , the protection of the rights of the subjects , and reduce the risk of clinical trials .
RESUMEN
A fast non-local means image denoising algorithm is presented based on the single motif of existing computed tomography images in medical archiving systems. The algorithm is carried out in two steps of prepossessing and actual possessing. The sample neighborhood database is created via the data structure of locality sensitive hashing in the prepossessing stage. The CT image noise is removed by non-local means algorithm based on the sample neighborhoods accessed fast by locality sensitive hashing. The experimental results showed that the proposed algorithm could greatly reduce the execution time, as compared to NLM, and effectively preserved the image edges and details.