Kun Wang
0000-0003-2513-768X
Chinese Academy of Sciences Institute of Automation
123 papers found
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L p Regularization for Bioluminescence Tomography Based on the Split Bregman Method
Targeted Aucore-Agshell nanorods as a dual-functional contrast agent for photoacoustic imaging and photothermal therapy
Intraoperative Identification of Liver Cancer Microfoci Using a Targeted Near-Infrared Fluorescent Probe for Imaging-Guided Surgery
Illuminating necrosis: From mechanistic exploration to preclinical application using fluorescence molecular imaging with indocyanine green
Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach
Salt-induced aggregation of gold nanoparticles for photoacoustic imaging and photothermal therapy of cancer
Precise diagnosis in different scenarios using photoacoustic and fluorescence imaging with dual-modality nanoparticles
Postreconstruction filtering of 3D PET images by using weighted higher-order singular value decomposition
Multispectral hybrid Cerenkov luminescence tomography based on the finite element SPn method
A Novel Endoscopic Cerenkov Luminescence Imaging System for Intraoperative Surgical Navigation
In vivo nanoparticle-mediated radiopharmaceutical-excited fluorescence molecular imaging
Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit
Endoscopic Cerenkov luminescence imaging: in vivo small animal tumor model validation
In vivobioluminescence tomography based on multi-view projection and 3D surface reconstruction
Optical Molecular Imaging Frontiers in Oncology: The Pursuit of Accuracy and Sensitivity
From PET/CT to PET/MRI: Advances in Instrumentation and Clinical Applications
Probability method for Cerenkov luminescence tomography based on conformance error minimization
Novel fusion for hybrid optical/microcomputed tomography imaging based on natural light surface reconstruction and iterated closest point
Optical molecular imaging: A review of recent progression and applications in oncology
Bioluminescence Tomography by an Iterative Reweighted <formula formulatype="inline"><tex Notation="TeX">${\bm {l_{2}}}$</tex></formula>-Norm Optimization
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