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reactional相关的网络例句

查询词典 reactional

与 reactional 相关的网络例句 [注:此内容来源于网络,仅供参考]

This research has proved that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化

Therefore, the percents of reactional enhancement cases and tumor residual cases employed in this research are 50% respectively, which enables the network to study the magnetic resonance image characteristics of the two "justly".

因此,本研究所用数据反应性强化与肿瘤残存病例各约占50%,使网络能&公正&地学习二者的磁共振影像特点。

This research has prove d that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化

This research has proved that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual. As a innovative differentiation approach, it requires further studies and researches to determine its applicability in practice, including the increase of training samples, image description standardization, effects to doctoral diagnosis, as well as parameter optimization. With improvements in these elements, the performance of the network will be optimized.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化,为解决二者的鉴别这一复杂问题提供了一个新的方法,但是本研究只是初步的应用探讨,能否在实际中应用,还有待于进一步的研究,如训练样本的增加、图像描述的规范化、对医师诊断影响程度、参数的优化等,网络的性能会不断完善和提高。

From these experiments, the optinum condition was chosen. The comparison of the reactional results of different degree of deacetylation chitosan with those of N-substitute chitosan und...

在相同条件下,比较不同脱乙酰度甲壳胺及N-取代甲壳胺的接枝聚合反应结果,表明:甲壳胺中氨基参与了接枝聚合反应的引发过程。

Therefore, the percents of reactional enhancement cases and tumor residual cases employed in this research are 50% respectively, which enables the network to study the magnetic resonance image characteristic s of the two "justly".

因此,本研究所用数据反应性强化与肿瘤残存病例各约占50%,使网络能&公正&地学习二者的磁共振影像特点。

This research has proved that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual. As a innovative differentiation approach, it requires further studies and researches to determine its applicability in practice, including the increase of training samples, image de脚本ion standardization, effects to doctoral diagnosis, as well as parameter optimization. With improvements in these elements, the performance of the network will be optimized.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化,为解决二者的鉴别这一复杂问题提供了一个新的方法,但是本研究只是初步的应用探讨,能否在实际中应用,还有待于进一步的研究,如训练样本的增加、图像描述的规范化、对医师诊断影响程度、参数的优化等,网络的性能会不断完善和提高。

The prepara tion,characterization,mechanism,the effect on shells from reactional condi-t ion and the development trend of hollow spheres are summarized.

本文介绍了纳米金属氧化物空心球的制备及表征方法,并对其形成机理、反应条件对壳层的影响以及存在的问题及今后的发展方向进行了初步探讨。

Therefore, the percents of reactional enhancement cases and tumor residual cases employ ed in this research are 50% respectively, which enables the network to study the magnetic resonance image characteristics of the two "justly".

因此,本研究所用数据反应性强化与肿瘤残存病例各约占50%,使网络能&公正&地学习二者的磁共振影像特点。

Sources have it that the incidence rate of intracranial gliomas postoperative reactional enhancement is 65.7%, whereas that of tumor residual is 34.3%.

据文献报道,胶质瘤术后反应性强化的发生率是65.7%,肿瘤残存发生率是34.3

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