International journal of biomedical research & practice最新文献

英文中文

Limited-Angle Tomography Using a Neural Network as the Objective Function. 以神经网络为目标函数的有限角度断层扫描。

International journal of biomedical research & practice

Pub Date : 2025-01-01 Epub Date: 2025-07-30

Gengsheng L Zeng

In limited-angle tomography, the system of imaging equations is underdetermined, and a naïve reconstruction may not have any practical values. Additional information is needed to augment the data so that a useful image can be reconstructed. This additional information is usually implemented as a Bayesian term in the objective function for an iterative optimization procedure. The state-of-the-art augmented information is the total variation (TV) norm of the image. The TV norm enforces a smooth image with sharp edges. The novelty of this paper is a new Bayesian term that is in the form of a neural network. This neural network is a classifier trained by images reconstructed by full and limited-angle projections. The impact of the proposed method is that the information provided by the neural network contains more features of the images than the TV norm and better reconstruction is expected. Computer simulations are carried out and presented.

在有限角度断层摄影中，成像方程系统是不确定的，并且naïve重建可能没有任何实用价值。需要额外的信息来增强数据，以便重建有用的图像。这些附加信息通常作为迭代优化过程的目标函数中的贝叶斯项来实现。最先进的增强信息是图像的总变分（TV）范数。电视规范要求画面平滑，边缘锐利。本文的新颖之处在于一个新的贝叶斯术语，它以神经网络的形式出现。该神经网络是由全角度和有限角度投影重建的图像训练而成的分类器。该方法的影响在于，神经网络提供的信息比电视规范包含了更多的图像特征，并且有望获得更好的重建效果。并进行了计算机仿真。

引用次数: 0

One-Step Image Reconstruction for Cine MRI with a Quadratic Constraint. 带二次约束的线性磁共振成像的一步式图像重建

International journal of biomedical research & practice

Pub Date : 2024-01-01 Epub Date: 2024-06-16 DOI: 10.33425/2769-6294.1029

Gengsheng L Zeng, Xiaodong Ma, Chun Yuan

Motivation: In cine MRI, the measurements within each timeframe alone are too noisy for image reconstruction. Some information must be 'borrowed' from other time frames and the reconstruction algorithm is a slow iterative procedure.

Goals: We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction. We derive a non-iterative algorithm to minimize this objective function.

Approach: The derivation of the algorithm is based on the calculus of variations. The resultant algorithm is in the form of filtered backprojection.

Results: The feasibility of the proposed algorithm is demonstrated with a clinical patient brain study.

Impact: Non-iterative reconstruction that minimizes a constrained objective function significantly increases the throughput in healthcare institutions. This may translate to reduced healthcare costs. The new reconstruction formula has a closed form that gives an explicit expression of how to incorporate the reference image in dynamic reconstruction.

动机：在电影MRI中，单独在每个时间框架内的测量噪声太大，无法进行图像重建。一些信息必须从其他时间框架中“借用”，重建算法是一个缓慢的迭代过程。目的：建立约束目标函数，利用其他时间帧的测量值对图像重建进行正则化。我们推导了一个非迭代算法来最小化这个目标函数。方法：算法的推导基于变分法。所得到的算法是滤波后的反向投影。结果：通过临床患者大脑研究证明了该算法的可行性。影响：最小化约束目标函数的非迭代重建显著提高了医疗机构的吞吐量。这可能转化为降低医疗成本。新的重建公式具有封闭的形式，明确地表达了如何在动态重建中纳入参考图像。

{"title":"One-Step Image Reconstruction for Cine MRI with a Quadratic Constraint.","authors":"Gengsheng L Zeng, Xiaodong Ma, Chun Yuan","doi":"10.33425/2769-6294.1029","DOIUrl":"10.33425/2769-6294.1029","url":null,"abstract":"Motivation: In cine MRI, the measurements within each timeframe alone are too noisy for image reconstruction. Some information must be 'borrowed' from other time frames and the reconstruction algorithm is a slow iterative procedure.Goals: We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction. We derive a non-iterative algorithm to minimize this objective function.Approach: The derivation of the algorithm is based on the calculus of variations. The resultant algorithm is in the form of filtered backprojection.Results: The feasibility of the proposed algorithm is demonstrated with a clinical patient brain study.Impact: Non-iterative reconstruction that minimizes a constrained objective function significantly increases the throughput in healthcare institutions. This may translate to reduced healthcare costs. The new reconstruction formula has a closed form that gives an explicit expression of how to incorporate the reference image in dynamic reconstruction.","PeriodicalId":520232,"journal":{"name":"International journal of biomedical research & practice","volume":"4 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11670894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142901587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Better than the Total Variation Regularization. 优于总变异正则化。

International journal of biomedical research & practice

Pub Date : 2024-01-01 Epub Date: 2024-06-21

Gengsheng L Zeng

The total variation (TV) regularization is popular in iterative image reconstruction when the piecewise-constant nature of the image is encouraged. As a matter of fact, the TV regularization is not strong enough to enforce the piecewise-constant appearance. This paper suggests a different regularization function that is able to discourage some smooth transitions in the image and to encourage the piecewise-constant behavior. This new regularization function involves a Gaussian function. We use the limited-angle tomography problem to illustrate the effectiveness of this new regularization function. The limited-angle tomography situation considered in this paper uses a scanning angular range of $40 °$ . For two-dimensional parallel-beam imaging, the required angular range is supposed to be $180 °$ .

总变化（TV）正则化在迭代图像重建中很受欢迎，因为它鼓励图像的片断不变性。事实上，TV 正则化的强度不足以实现片断不变的外观。本文提出了一种不同的正则化函数，它能够抑制图像中的一些平滑过渡，并鼓励片断恒定行为。这种新的正则化函数涉及一个高斯函数。我们使用有限角度断层扫描问题来说明这种新正则化函数的有效性。本文考虑的有限角度断层扫描情况使用 40 ° 的扫描角度范围。对于二维平行光束成像，所需的角度范围应该是 180 °。

引用次数: 0

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

International journal of biomedical research & practice

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀