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Your search keyword '"Di, Fang‐Fang"' showing total 8 results
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8 results on '"Di, Fang‐Fang"'

7. Crown Ether Host‐Guest Molecular Ferroelectrics.

Author

Zhang, Yun‐Fang, Di, Fang‐Fang, Li, Peng‐Fei, and Xiong, Ren‐Gen

Subjects
*CROWN ethers, *FERROELECTRIC crystals, *ORDER-disorder transitions, *FERROELECTRIC transitions, *PHASE transitions
Abstract

In recent years, molecular ferroelectrics have received great attention due to their low weight, mechanical flexibility, easy preparation and excellent ferroelectric properties. Among them, crown‐ether‐based molecular ferroelectrics, which are typically composed of the host crown ethers, the guest cations anchored in the crown ethers, and the counterions, are of great interest because of the host‐guest structure. Such a structure allows the components to occur order‐disorder transition easily, which is beneficial for inducing ferroelectric phase transition. Herein, we summarized the research progress of crown ether host‐guest molecular ferroelectrics, focusing on their crystal structure, phase transition, ferroelectric‐related properties. In view of the small spontaneous polarization and uniaxial nature, we outlook the chemical design strategies for obtaining high‐performance crown‐ether‐based molecular ferroelectrics. This minireview will be of guiding significance for the future exploration of crown ether host‐guest molecular ferroelectrics. [ABSTRACT FROM AUTHOR]

Published
2022
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8. A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information

Author

Libo Zhang, Huiyan Jiang, Benqiang Yang, Zhiyuan Ma, Di Fang Fang Fang, and Baochun He

Subjects
Models, Anatomic, Article Subject, Computer science, lcsh:Computer applications to medicine. Medical informatics, General Biochemistry, Genetics and Molecular Biology, symbols.namesake, Imaging, Three-Dimensional, Region of interest, Humans, Computer vision, Computer Simulation, General Immunology and Microbiology, Fourier Analysis, business.industry, Applied Mathematics, Spectrum (functional analysis), Models, Cardiovascular, Retinal Vessels, General Medicine, Fourier transform, Liver, Region growing, Feature (computer vision), Fourier analysis, Modeling and Simulation, symbols, lcsh:R858-859.7, Blood Vessels, Enhanced Data Rates for GSM Evolution, Tomography, Artificial intelligence, business, Tomography, X-Ray Computed, Algorithm, Algorithms, Research Article
Abstract

We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure’s center points as the seed points of region growing segmentation. At last, the improved region growing method with branch-based growth strategy is used to segment the vessels. To prove the effectiveness of our algorithm, we use the retinal and abdomen liver vascular CT images to do experiments. The results show that the proposed vessel segmentation algorithm can not only extract the high quality target vessel region, but also can effectively reduce the manual intervention.

Published
2013
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