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472 results on '"Wang, L.W."'

114. VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images

Author

Sekuboyina, A., Husseini, M.E., Bayat, A., Loffler, M., Liebl, H., Li, H., Tetteh, G., Kukacka, J., Payer, C., Stern, D., Urschler, M., Chen, M., Cheng, D., Lessmann, N., Hu, Y., Wang, T., Yang, D., Xu, D., Ambellan, F., Amiranashvili, T., Ehlke, M., Lamecker, H., Lehnert, S., Lirio, M., Olaguer, N.P., Ramm, H., Sahu, M., Tack, A., Zachow, S., Jiang, T., Ma, X., Angerman, C., Wang, X, Brown, K., Kirszenberg, A., Puybareau, E., Chen, D., Bai, Y., Rapazzo, B.H., Yeah, T., Zhang, A., Xu, S., Hou, F., He, Z., Zeng, C., Xiangshang, Z., Liming, X., Netherton, T.J., Mumme, R.P., Court, L.E., Huang, Z., He, C., Wang, L.W., Ling, S.H., Huynh, L.D., Boutry, N., Jakubicek, R., Chmelik, J., Mulay, S., Sivaprakasam, M., Paetzold, J.C., Shit, S., Ezhov, I., Wiestler, B., Glocker, B., Valentinitsch, A., Rempfler, M., Menze, B.H., Kirschke, J.S., Sekuboyina, A., Husseini, M.E., Bayat, A., Loffler, M., Liebl, H., Li, H., Tetteh, G., Kukacka, J., Payer, C., Stern, D., Urschler, M., Chen, M., Cheng, D., Lessmann, N., Hu, Y., Wang, T., Yang, D., Xu, D., Ambellan, F., Amiranashvili, T., Ehlke, M., Lamecker, H., Lehnert, S., Lirio, M., Olaguer, N.P., Ramm, H., Sahu, M., Tack, A., Zachow, S., Jiang, T., Ma, X., Angerman, C., Wang, X, Brown, K., Kirszenberg, A., Puybareau, E., Chen, D., Bai, Y., Rapazzo, B.H., Yeah, T., Zhang, A., Xu, S., Hou, F., He, Z., Zeng, C., Xiangshang, Z., Liming, X., Netherton, T.J., Mumme, R.P., Court, L.E., Huang, Z., He, C., Wang, L.W., Ling, S.H., Huynh, L.D., Boutry, N., Jakubicek, R., Chmelik, J., Mulay, S., Sivaprakasam, M., Paetzold, J.C., Shit, S., Ezhov, I., Wiestler, B., Glocker, B., Valentinitsch, A., Rempfler, M., Menze, B.H., and Kirschke, J.S.

Abstract

Contains fulltext : 238698.pdf (Publisher’s version ) (Open Access), Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.

Published
2021

139. Comparison of two methods for describing the strain profiles in quantum dots

Author

Pryor, C., Kim, J., Wang, L.W., Williamson, A.J., and Zunger, A.

Subjects
Quantum electrodynamics -- Research, Semiconductors -- Research, Gallium arsenide semiconductors -- Research, Physics
Abstract

Research was conducted to study techniques for computing strain profiles associated with the electronic structure of interfaces between lattice-mismatched gallium arsenide semiconductors. The strain energy was expressed as a function of atomic positions while elastic constants of valence force field method were evaluated using alpha and beta figures. Results showed differences in the strain around the dot interfaces and inside the dot.

Published
1998

148. Deposition of scintillating layers of bismuth germanate (BGO) films for X-ray detector applications

Author

Duan, M., Frojdh, C., Thungstrom, G., Wang, L.W., Linnros, J., and Petersson, C.S.

Subjects
Nuclear research -- Materials, X-ray crystallography -- Equipment and supplies, X-rays -- Research, Metallic oxides -- Research, Business, Electronics, Electronics and electrical industries
Abstract

[Bi.sub.4][Ge.sub.3][O.sub.12] films were deposited by pulsed laser ablation on glass and Si[O.sub.2]/Si substrates. The crystal structures of the films depend on the deposition temperature. XRD patterns indicate that the films deposited at substrate temperature less than 400 [degrees] C are amorphous. The as deposited amorphous films can be crystallized by post rapid thermal annealing (RTA) in the temperature window from 750 [degrees] C to 800 [degrees] C for 2 minutes in a oxygen ambient environment. RBS measurements confirm that the films have the same chemical composition as that of the target. The surface morphology of the films were characterized by atomic force microscopy(AFM).

Published
1998

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