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RISS 인기검색어
- 검색키워드
- 저자 : Yanrong Dong (검색결과 4 건)
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Robust brain ROI segmentation by deformation regression and deformable shape model
Wu, Zhengwang,Guo, Yanrong,Park, Sang Hyun,Gao, Yaozong,Dong, Pei,Lee, Seong-Whan,Shen, Dinggang Elsevier 2018 Medical image analysis Vol.43 No.-
<P><B>Abstract</B></P> <P>We propose a robust and efficient learning-based deformable model for segmenting regions of interest (ROIs) from structural MR brain images. Different from the conventional deformable-model-based methods that deform a shape model locally around the initialization location, we learn an image-based regressor to guide the deformable model to fit for the target ROI. Specifically, given any voxel in a new image, the image-based regressor can predict the displacement vector from this voxel towards the boundary of target ROI, which can be used to guide the deformable segmentation. By predicting the displacement vector maps for the whole image, our deformable model is able to use multiple non-boundary predictions to jointly determine and iteratively converge the initial shape model to the target ROI boundary, which is more robust to the local prediction error and initialization. In addition, by introducing the prior shape model, our segmentation avoids the isolated segmentations as often occurred in the previous multi-atlas-based methods. In order to learn an image-based regressor for displacement vector prediction, we adopt the following novel strategies in the learning procedure: (1) a joint classification and regression random forest is proposed to learn an image-based regressor together with an ROI classifier in a multi-task manner; (2) high-level context features are extracted from intermediate (estimated) displacement vector and classification maps to enforce the relationship between predicted displacement vectors at neighboring voxels. To validate our method, we compare it with the state-of-the-art multi-atlas-based methods and other learning-based methods on three public brain MR datasets. The results consistently show that our method is better in terms of both segmentation accuracy and computational efficiency.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A learning-based deformable model segmentation method is proposed, which is not sensitive to initialization. </LI> <LI> Smooth segmentation of the whole brain ROIs is obtained by introducing the prior brain ROI shape information. </LI> <LI> Validated on 3 popular datasets, our method achieves the best performance. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
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Zhang, Guobing,Dai, Yanrong,Wang, Dong,Liu, Yu,Lu, Hongbo,Qiu, Longzhen,Cho, Kilwon Elsevier 2017 Dyes and pigments Vol.147 No.-
<P><B>Abstract</B></P> <P>A new thieno-isoindigo derivative, (3<I>E</I>,7<I>E</I>)-3,7-bis(4-(2-decyltetradecyl)-4<I>H</I>-thieno[3,2-<I>b</I>]pyrrole-5,6-dione)-5,7-dihydropyrrolo[2,3-<I>f</I>]indole-2,6(1<I>H</I>,3<I>H</I>)-dione (<B>BTPDI</B>), was designed and synthesized. A donor−acceptor conjugated polymer (<B>PBTPDI-TT</B>) was also synthesized with this new unit as the acceptor and thieno[3,2-<I>b</I>]thiophene as the donor. The microstructure, photophysical, electrochemical, field-effect properties and photothermal performances were investigated. The polymer showed a broad absorption spectrum that spanned across the near-infrared (NIR) region (780–1300 nm), with a very low bandgap (∼0.95 eV), deep lowest unoccupied molecular orbital, and suitable highest occupied molecular orbital levels. As a result, the polymer-based organic field-effect transistors showed highly balanced hole and electron transport characteristics with a hole mobility of 0.027 cm<SUP>2</SUP> V<SUP>−1</SUP>s<SUP>−1</SUP> and an electron mobility of 0.022 cm<SUP>2</SUP> V<SUP>−1</SUP>s<SUP>−1</SUP>. The polymer nanoparticles showed good reusability under NIR (980 nm) irradiation and could also effectively convert NIR light to heat at an excellent efficiency of 20.3%.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A new thieno-isoindigo derivative dye and its polymer were designed and synthesized. </LI> <LI> The polymer showed ultra broad absorption spectra that spanned across the near-infrared region and remarkably low bandgap. </LI> <LI> The new polymer showed highly balanced hole and electron transport characteristics. </LI> <LI> Polymer nanoparticles showed excellent photothermal conversion efficiency under 980 nm irradiation. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
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Xianjun Wang,Junzhen Di,Bing Liang,Yu Yang,Yanrong Dong,Mingxin Wang 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.5
In view of the serious pollution and high cost of treatment of acid mine drainage (AMD) in coal mine, the polyving akohol (PVA) and boric acid embedding cross-linking method was used to prepare the immobilized particles for treatment of AMD with sulfate-reducing bacteria (SRB) and nano zero-valent iron (nano-Fe⁰) as the main body. In order to explore the specification and dosage of each matrix component of immobilized particle, a series of single factor tests and orthogonal tests were carried out to determine the optimal ratio of each matrix component. The results shows that when the SRB quality additive percentage was 30%, the nano-Fe0 dosage was 4%, the corn cob particle size was 60 mesh and the dosage was 3%, the SO₄<SUP>2-</SUP>, Cr<SUP>6+</SUP> and Cr<SUP>3+</SUP> removal rates were 82.99%, 99.78% and 38.78%, respectively, the TFe and COD release rates were 4.26 ㎎·L<SUP>-1</SUP> and 1,033.4 ㎎·L<SUP>-1</SUP>, respectively, and the pH value was 8.04, and the treatment effect was the best.
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Sihang Bao,Junzhen Di,Jianguo Yang,Donglin Wang,Juan Sun,Yanrong Dong 대한환경공학회 2022 Environmental Engineering Research Vol.27 No.3
In view of the high content of Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> in acid mine drainage (AMD), the adsorption properties of lignite for Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> were studied. The adsorption performance of lignite for Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> was revealed by combining with FT-IR, XPS and EDS. The results showed that the adsorption kinetic model of lignite for Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> conformed to the quasi-first-order kinetic model. The isothermal adsorption line fitting models of lignite for Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> were in accordance with the Langmuir model and the Freundlich model, respectively. The maximum equilibrium adsorption capacities of lignite for Cu and Zn were 67.84 mg/g and 55.5 mg/g. The adsorption process of Cu<SUP>2+</SUP> and Zn<SUP>2+</SUP> by lignite involved electrostatic, coordination and ion exchange. Under the condition of coexistence of two kinds of ion, the adsorption site of lignite had stronger binding ability to copper ions.
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