Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences

1999 ◽  
Vol 18 (5) ◽  
pp. 429-441 ◽  
Author(s):  
J.-P. Thirion ◽  
G. Calmon
Keyword(s):  
Medical Image ◽  
Three Dimensional ◽  
Image Sequences ◽  
Deformation Analysis

Three-dimensional separate descendant-based SPIHT algorithm for fast compression of high-resolution medical image sequences

2017 ◽  
Vol 11 (1) ◽  
pp. 80-87 ◽  
Author(s):  
Xiaoying Song ◽  
Qijun Huang ◽  
Sheng Chang ◽  
Jin He ◽  
Hao Wang
Keyword(s):  
High Resolution ◽  
Medical Image ◽  
Three Dimensional ◽  
Image Sequences ◽  
Spiht Algorithm

Optimization and Implementation of the Surface Rendering Algorithm

2011 ◽  
Vol 341-342 ◽  
pp. 152-157
Author(s):  
Chen Liang ◽  
Nan Jiang ◽  
Ya Wen Yu
Keyword(s):  
Medical Image ◽  
High Efficiency ◽  
Three Dimensional ◽  
Image Sequences ◽  
Research Field ◽  
Accurate Information ◽  
Surface Rendering ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Normal Tissues

Three-dimensional visualization of medical imaging technology uses two-dimensional medical image sequences to reconstruct three-dimensional model, providing the physician with intuitive, comprehensive, accurate information about the focus and normal tissues, is currently a hot research field of medicine. This essay makes a comparison between the two currently popular algorithms – surface rendering algorithm and volume rendering algorithm, with its focus on the introduction of MC algorithm, meanwhile achieves the integration of three types of improved MC algorithm, completes a high-precision, high-efficiency surface rendering process based on .MFC and OpenGL technologies.

Three-dimensional Medical Image Segmentation with SE-VNet Neural Networks

2021 ◽  
Author(s):  
Sheng Lu ◽  
Jungang Han ◽  
Jiantao Li ◽  
Liyang Zhu ◽  
Jiewei Jiang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Image Segmentation ◽  
Medical Image ◽  
Three Dimensional ◽  
Medical Image Segmentation

scholarly journals Network method for deformation analysis of three-dimensional point cloud with terrestrial laser scanning sensor

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881413 ◽  
Author(s):  
Xiangyang Xu ◽  
Hao Yang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Deformation Analysis ◽  
Transverse Displacement ◽  
Displacement Analysis ◽  
Accuracy Measurement ◽  
Network Method ◽  
Displacement Information

The complexity of structural materials is increasing the importance of the technology for high accuracy measurement. How to obtain the displacement information of structural feature points accurately and efficiently is the key issue of deformation analysis. In this article, displacement analysis of a composite arched structure is investigated based on the terrestrial laser scanning technique. A new method based on the measured point cloud is proposed to analyze the displacement of surficial points, resulting in not only the displacement size but also the displacement direction. The innovation lies in extracting the displacement information with a network and remapped point cloud, which is called the network method. The displacement map obtained demonstrates that the transverse displacement in the experiment plays an important role in the safety of the structure, which could not be observed and obtained by the surface approximation method. Therefore, the panorama- and pointwise displacement analysis technologies contribute to ensure the safety of increasingly complex constructions.

A Video Super Resolution Algorithm Based on Wavelet Coefficient

2014 ◽  
Vol 610 ◽  
pp. 425-428
Author(s):  
Wei Jian Liu ◽  
Si Da Xiao ◽  
Ruo He Yao
Keyword(s):  
High Frequency ◽  
Wavelet Coefficient ◽  
Three Dimensional ◽  
Super Resolution ◽  
Structural Similarity ◽  
Image Sequences ◽  
Discrete Wavelet ◽  
Resolution Image ◽  
Resolution Algorithm ◽  
Visual Results

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

scholarly journals Combined Local Global Optical Flow Approach in Bio-medical Image Sequences for blood flow detection

IJARCCE ◽  
2015 ◽  
pp. 468-473
Author(s):  
Kazi Md. Shahiduzzaman ◽  
Khan Mamun Reza ◽  
Nusrat Tazin
Keyword(s):  
Blood Flow ◽  
Optical Flow ◽  
Medical Image ◽  
Image Sequences ◽  
Flow Detection
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