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- 저자 : Chenghao Lin (검색결과 3 건)
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Zheyu Yang,Yu Heng,Jianwei Lin,Chenghao Lu,Dingye Yu,Lei Tao,Wei Cai 대한암학회 2020 Cancer Research and Treatment Vol.52 No.4
Purpose Central lymph node metastasis (CNM) are highly prevalent but hard to detect preoperatively in papillary thyroid carcinoma (PTC) patients, while the significance of prophylactic compartment central lymph node dissection (CLND) remains controversial as a treatment option. We aim to establish a nomogram assessing risks of CNM in PTC patients, and explore whether prophylactic CLND should be recommended. Materials and Methods One thousand four hundred thirty-eight patients from two clinical centers that underwent thyroidectomy with CLND for PTC within the period 2016-2019 were retrospectively analyzed. Univariate and multivariate analysis were performed to examine risk factors associated with CNM. A nomogram for predicting CNM was established, thereafter internally and externally validated. Results Seven variables were found to be significantly associated with CNM and were used to construct the model. These were as follows: thyroid capsular invasion, multifocality, creatinine > 70 μmol/L, age < 40, tumor size > 1 cm, body mass index < 22, and carcinoembryonic antigen > 1 ng/mL. The nomogram had good discrimination with a concordance index of 0.854 (95% confidence interval [CI], 0.843 to 0.867), supported by an external validation point estimate of 0.825 (95% CI, 0.793 to 0.857). A decision curve analysis was made to evaluate nomogram and ultrasonography for predicting CNM. Conclusion A validated nomogram utilizing readily available preoperative variables was developed to predict the probability of central lymph node metastases in patients presenting with PTC. This nomogram may help surgeons make appropriate surgical decisions in the management of PTC, especially in terms of whether prophylactic CLND is warranted.
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Investigation of the super-resolution methods for vision based structural measurement
Zhi Cong Chen,Lijun Wu,Zhouwei Cai,Chenghao Lin,Shuying Cheng,Peijie Lin 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.3
The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.
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Jin Yong,Wang Zhilin,Zhang Zhenxin,Lin Bo,Ge Zhengjun,You Qidong,Chen Hao,Liu Xiliang,Xu Chenghao,Gao Shuaiqiang,Wu Yi,Abro Zafar 한국자원공학회 2023 Geosystem engineering Vol.26 No.4
CO2 flooding is a significant technology for oil recovery, to reveal the microcosmic mechanism of CO2 flooding, CO2 slim tube experiments, long core CO2 flooding experiments, gas chromatography analysis experiments, and numerical simulations were carried out. The results show that the miscibility increase can improve the effect of dissolution and diffusion in the CO2-crude oil system, easing the CO2 finger entry phenomena, and delaying gas breakthrough time. Besides, the CO2 -crude oil interaction is enhanced by increasing the pressure difference between the injection well and the production well, which improves the oil recovery of CO2 flooding. Besides, CO2 carries the light and medium components (C4 ~ 25) forward to cross the first miscible zone, which makes the CO2-crude oil system form double miscible zones. This study reveals the rule of CO2 front and light components front under different miscibility degrees of CO2 flooding from the microscopic perspective and deepens the theory of CO2 flooding in low-permeability sandstone reservoirs.
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