Frontiers in biomolecular mesh generation and molecular visualization systems [0.03%]
生物分子网格生成及分子可视化系统研究进展
Sheng Gui,Dawar Khan,Qin Wang et al.
Sheng Gui et al.
With the development of biomolecular modeling and simulation, especially implicit solvent modeling, higher requirements are set for the stability, efficiency and mesh quality of molecular mesh generation software. In this review, we summari...
Energy enhanced tissue texture in spectral computed tomography for lesion classification [0.03%]
基于谱CT组织纹理能量特征的病灶分类
Yongfeng Gao,Yongyi Shi,Weiguo Cao et al.
Yongfeng Gao et al.
Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels, i.e., the tissue heterogeneity, and has been recognized as important biomarkers in various clinical tasks. Spectral computed tomography (CT) is believ...
Optimizing photoacoustic image reconstruction using cross-platform parallel computation [0.03%]
基于跨平台并行计算的光声成像优化重建方法
Tri Vu,Yuehang Wang,Jun Xia
Tri Vu
Three-dimensional (3D) image reconstruction involves the computations of an extensive amount of data that leads to tremendous processing time. Therefore, optimization is crucially needed to improve the performance and efficiency. With the w...
Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning [0.03%]
结合运动估计、补偿重建、生物力学建模和深度学习的先进四维锥形束计算成像重建技术
You Zhang,Xiaokun Huang,Jing Wang
You Zhang
4-Dimensional cone-beam computed tomography (4D-CBCT) offers several key advantages over conventional 3D-CBCT in moving target localization/delineation, structure de-blurring, target motion tracking, treatment dose accumulation and adaptive...
Adaptive deep learning for head and neck cancer detection using hyperspectral imaging [0.03%]
基于高光谱成像的自适应深度学习口腔肿瘤检测方法研究
Ling Ma,Guolan Lu,Dongsheng Wang et al.
Ling Ma et al.
It can be challenging to detect tumor margins during surgery for complete resection. The purpose of this work is to develop a novel learning method that learns the difference between the tumor and benign tissue adaptively for cancer detecti...
Developing global image feature analysis models to predict cancer risk and prognosis [0.03%]
开发全球图像特征分析模型以预测癌症风险和预后
Bin Zheng,Yuchen Qiu,Faranak Aghaei et al.
Bin Zheng et al.
In order to develop precision or personalized medicine, identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest recently. Most of the...
Extension of emission expectation maximization lookalike algorithms to Bayesian algorithms [0.03%]
发射期望最大化类似算法扩展到贝叶斯算法
Gengsheng L Zeng,Ya Li
Gengsheng L Zeng
We recently developed a family of image reconstruction algorithms that look like the emission maximum-likelihood expectation-maximization (ML-EM) algorithm. In this study, we extend these algorithms to Bayesian algorithms. The family of emi...