搜索结果: 1-15 共查到“Imaging”相关记录690条 . 查询时间(0.14 秒)
近日，医学部生物医学工程学院倪东教授团队在国际医学图像分析领域的顶级期刊《IEEE Transaction on Medical Imaging》（影响因子IF=10.6）上，发表了一篇题为“Semi-Supervised Representation Learning for Segmentation on Medical Volumes and Sequences”的高质量论文。深圳大学医学部...
Using state-of-the-art magnetic imaging, a Cornell-led collaboration has for the first time characterized a key property of the superconducting state of a class of atomically thin materials that are t...
Sodium-ion batteries have been touted as a sustainable alternative to lithium-ion batteries because they are powered by a more abundant natural resource. However, sodium-ion batteries have hit a signi...
近日，医学部生物医学工程学院汪天富、雷柏英教授团队在医学图像处理领域顶级期刊《IEEE Transactions on Medical Imaging》(中科院大类一区TOP期刊，IF：11.037)上发表了系列研究成果。
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Fast Magnetic Resonance Imaging and Inverse Problems
快速 磁共振成像 逆问题
2023/4/17
磁共振成像是目前医学成像技术中功能最强大，技术门槛最复杂的技术之一。然而，相对其他成像模态较为缓慢的采集速度（较长的扫描时间）制约了磁共振成像在临床上的广泛应用。借助采样样本的数量与扫描时间的正比关系，通过减少采集的数据量（稀疏采样）来缩短磁共振采集时间是磁共振成像领域的重要途径，而从高度欠采样的数据中重建出高质量的图像可以近似为一个病态反问题，对这一问题的求解是快速磁共振成像领域的研究热点。本次...
浙江大学光电科学与工程学院郝翔课题组论文《Spectral Imaging with Deep Learning》发表于《Light：Science & Applications》封面（图）
光谱成像 光学滤光片 光谱编码
2023/3/10
2022年6月17日，浙江大学光电科学与工程学院郝翔课题组综述文章《Spectral imaging with deep learning》发表于《Light:Science&Applications》杂志第六期封面。该研究回顾了光谱成像技术应用深度学习的最新进展，对基于深度学习的光谱成像技术进行了梳理。研究对深度学习光谱成像的各种技术路线进行了原理阐述、研究总结，并整理了当前的光谱成像数据集、概...
Tests conducted by Cornell and the U.S. Navy used new algorithms to outperform state-of-the-art programming for autonomous underwater sonar imaging, significantly improving the speed and accuracy for ...
Enabling Breeding Selection for Biomass in Slash Pine Using UAV-Based Imaging
Slash Pine Breeding Selection Biomass
2023/6/2
Background: Traditional methods used to monitor the aboveground biomass (AGB) and belowground biomass (BGB) of slash pine (Pinus elliottii) rely on on-ground measurements, which are time- and cost-con...
《IEEE Transactions on Medical Imaging》报道应用基于神经网络架构搜索和多模态成像的术中胶质瘤分级技术（图）
神经网络架构 胶质瘤 多模态成像 医学图像
2022/9/9
术中胶质瘤分级有助于制定临床治疗计划并改善预后，但术中冰冻切片病理检查因处理时间长、程序复杂而受到限制。近红外荧光成像为快速准确的实时诊断提供了机会，与神经网络/深度学习技术的融合被认为是最有前景的研究方向。然而，近红外荧光图像的小尺度、噪声和低分辨率等问题增加了网络的训练难度。多模态成像可以提供更多的信息以提高模型性能，但设计合适网络的同时利用多模态信息数据具有挑战性。
More sensitive X-ray imaging（图）
X射线成像 光材料 闪烁体
2023/6/7
Scintillators are materials that emit light when bombarded with high-energy particles or X-rays. In medical or dental X-ray systems, they convert incoming X-ray radiation into visible light that can t...
Estimation of Plant Height and Aboveground Biomass of Toona sinensis under Drought Stress Using RGB-D Imaging
Plant Height Aboveground Biomass Toona sinensis
2023/6/2
Background: Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used ...
近期，深圳大学医学部生物医学工程学院黄炳升副教授团队的研究成果《3D Lightweight Network for Simultaneous Registration and Segmentation of Organs-at-Risk in CT Images of Head and Neck Cancer》在医学图像分析领域的顶级期刊IEEE Transactions on Medical ...
Microscopists have long sought a way to produce high-quality, deep-tissue imaging of living subjects in a timely fashion. To date, they have had to choose between image quality or speed when looking i...
Coming soon to a lab tabletop near you: a method of magneto-thermal imaging that offers nanoscale and picosecond resolution previously available only in synchrotron facilities.
Century-old problem solved with first-ever 3D atomic imaging of an amorphous solid（图）
Century-old problem solved first-ever 3D atomic imaging amorphous solid
2021/4/16
Glass, rubber and plastics all belong to a class of matter called amorphous solids. In spite of how common they are in our everyday lives, amorphous solids have long posed a challenge to scientists.Si...