0000000000266171
AUTHOR
Hongkai Wang
showing 11 related works from this author
J/ψ suppression at forward rapidity in Pb–Pb collisions at sNN=5.02 TeV
2017
The inclusive J/$\psi$ production has been studied in Pn-Pb and pp collisions at the centre-of-mass energy per nucleon pair $\sqrt{s_{\rm NN}}=5.02$ TeV, using the ALICE detector at the CERN LHC. The J/$\psi$ meson is reconstructed, in the centre-of-mass rapidity interval $2.5<y<4$ and in the transverse-momentum range $p_{\rm T}<12$ GeV/$c$, via its decay to a muon pair. In this Letter, we present results on the inclusive J/$\psi$ cross section in pp collisions at $\sqrt{s}=5.02$ TeV and on the nuclear modification factor $R_{\rm AA}$. The latter is presented as a function of the centrality of the collision and, for central collisions, as a function of the transverse momentum $p_{\rm T}$ of…
Registration-based Construction of a Whole-body Human Phantom Library for Anthropometric Modeling.
2020
Various computational human phantoms have been proposed in the past decades, but few of them include delicate anthropometric variations. In this study, we build a whole-body phantom library including 145 anthropometric parameters. This library is constructed by registration-based pipeline, which transfers a standard whole-body anatomy template to an anthropometry-adjustable body shape library (MakeHuman™). Therefore, internal anatomical structures are created for body shapes of different anthropometric parameters. Based on the constructed library, we can generate individualized whole-body phantoms according to given arbitrary anthropometric parameters. Moreover, the proposed phantom library…
AnatomySketch : An Extensible Open-Source Software Platform for Medical Image Analysis Algorithm Development
2021
AbstractThe development of medical image analysis algorithm is a complex process including the multiple sub-steps of model training, data visualization, human–computer interaction and graphical user interface (GUI) construction. To accelerate the development process, algorithm developers need a software tool to assist with all the sub-steps so that they can focus on the core function implementation. Especially, for the development of deep learning (DL) algorithms, a software tool supporting training data annotation and GUI construction is highly desired. In this work, we constructed AnatomySketch, an extensible open-source software platform with a friendly GUI and a flexible plugin interfac…
Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images
2022
Abstract Purpose Training deep neural networks usually require a large number of human-annotated data. For organ segmentation from volumetric medical images, human annotation is tedious and inefficient. To save human labour and to accelerate the training process, the strategy of annotation by iterative deep learning recently becomes popular in the research community. However, due to the lack of domain knowledge or efficient human-interaction tools, the current AID methods still suffer from long training time and high annotation burden. Methods We develop a contour-based annotation by iterative deep learning (AID) algorithm which uses boundary representation instead of voxel labels to incorp…
Neutral pion and η meson production at midrapidity in Pb-Pb collisions at sNN=2.76 TeV
2018
Neutral pion and η meson production in the transverse momentum range 1 <pT< 20 GeV/c have been measured at midrapidity by the ALICE experiment at the Large Hadron Collider (LHC) in central and semicentral Pb-Pb collisions at sNN = 2.76 TeV. These results were obtained using the photon conversion method as well as the Photon Spectrometer (PHOS) and Electromagnetic Calorimeter detectors. The results extend the upper pT reach of the previous ALICE π0 measurements from 12 to 20 GeV/c and present the first measurement of η meson production in heavy-ion collisions at the LHC. The η/π0 ratio is similar for the two centralities and reaches at high pT a plateau value of 0.457 ± 0.013stat ± 0.018sys…
Constraints on jet quenching in p–Pb collisions at sNN=5.02 TeV measured by the event-activity dependence of semi-inclusive hadron-jet distributions
2018
The ALICE Collaboration reports the measurement of semi-inclusive distributions of charged-particle jets recoiling from a high-transverse momentum trigger hadron in p–Pb collisions at √sNN = 5.02 TeV. Jets are reconstructed from charged-particle tracks using the anti-kT algorithm with resolution parameter R = 0.2 and 0.4. A data-driven statistical approach is used to correct the uncorrelated background jet yield. Recoil jet distributions are reported for jet transverse momentum 15 < pch T,jet < 50 GeV/c and are compared in various intervals of p–Pb event activity, based on charged-particle multiplicity and zero-degree neutral energy in the forward (Pb-going) direction. The semi-inclusive ob…
Search for collectivity with azimuthal J/ψ-hadron correlations in high multiplicity p–Pb collisions at sNN=5.02 and 8.16 TeV
2018
A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences and Nationalstiftung fur Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Universidade Federal do Rio Grande do Sul (UFRGS), Financiadora de Estudos e Projetos (Finep) and Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazil; Ministry of Science & Technology of China (MSTC), National Natural Science Foundation of Chi…
Jet-like correlations with neutral pion triggers in pp and central Pb–Pb collisions at 2.76 TeV
2016
Physics letters / B B763, 238 - 250 (2016). doi:10.1016/j.physletb.2016.10.048
Lung CT Image Registration through Landmark-constrained Learning with Convolutional Neural Network
2020
Accurate registration of lung computed tomography (CT) image is a significant task in thorax image analysis. Recently deep learning-based medical image registration methods develop fast and achieve promising performance on accuracy and speed. However, most of them learned the deformation field through intensity similarity but ignored the importance of aligning anatomical landmarks (e.g., the branch points of airway and vessels). Accurate alignment of anatomical landmarks is essential for obtaining anatomically correct registration. In this work, we propose landmark constrained learning with a convolutional neural network (CNN) for lung CT registration. Experimental results of 40 lung 3D CT …
Automatic Segmentation of Pulmonary Lobes in Pulmonary CT Images using Atlas-based Unsupervised Learning Network
2020
Pulmonary lobes segmentation of pulmonary CT images is important for assistant therapy and diagnosis of pulmonary disease in many clinical tasks. Recently supervised deep learning methods are applied widely in fast automatic medical image segmentation including pulmonary lobes segmentation of pulmonary CT images. However, they require plenty of ground truth due to their supervised learning scheme, which are always difficult to realize in practice. To address this issue, in this study we extend an existed unsupervised learning network with an extra pulmonary mask constraint to develop a deformable pulmonary lobes atlas and apply it for fast automatic segmentation of pulmonary lobes in pulmon…
A Statistical Model of Spine Shape and Material for Population-Oriented Biomechanical Simulation
2021
In population-oriented ergonomics product design and musculoskeletal kinetics analysis, digital spine models of different shape, pose and material property are in great demand. The purpose of this study was to construct a parameterized finite element spine model with adjustable spine shape and material property. We used statistical shape model approach to learn inter-subject shape variations from 65 CT images of training subjects. Second order polynomial regression was used to model the age-dependent changes in vertebral material property derived from spatially aligned CT images. Finally, a parametric spine generator was developed to create finite element instances of different shapes and m…