共查询到20条相似文献，搜索用时 15 毫秒
1.
B. Priestly Shan O. Jeba Shiney Sharzeel Saleem V. Rajinikanth Atef Zaguia Dilbag Singh 《计算机、材料和连续体（英文）》2022,72(2):2749-2763
Low contrast of Magnetic Resonance (MR) images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis. State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images. Drastic changes in brightness features, induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings. To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well. This method termed as Power-law and Logarithmic Modification-based Histogram Equalization (PLMHE) partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression. After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization, cumulative histograms are computed. Enhanced grey level values are computed from the resultant cumulative histograms. The performance of the PLMHE algorithm is compared with traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression, a significant change in mean brightness, and contrast-overshoot. 相似文献
2.
本文详细介绍了人体正常组织中各种组分的磁共振（MR）信号、包括骨骼、肌肉、脂肪、软骨、水分、气体、血流、淋巴结等,以及发生病变时各种临床症状的特殊MR信号,是从事MR工作的医务人员必须掌握的基本实际知识。 相似文献
3.
Sujeet More Jimmy Singla Oh-Young Song Usman Tariq Sharaf Malebary 《计算机、材料和连续体（英文）》2021,69(3):3127-3143
Medical Resonance Imaging (MRI) is a noninvasive, nonradioactive, and meticulous diagnostic modality capability in the field of medical imaging. However, the efficiency of MR image reconstruction is affected by its bulky image sets and slow process implementation. Therefore, to obtain a high-quality reconstructed image we presented a sparse aware noise removal technique that uses convolution neural network (SANR_CNN) for eliminating noise and improving the MR image reconstruction quality. The proposed noise removal or denoising technique adopts a fast CNN architecture that aids in training larger datasets with improved quality, and SARN algorithm is used for building a dictionary learning technique for denoising large image datasets. The proposed SANR_CNN model also preserves the details and edges in the image during reconstruction. An experiment was conducted to analyze the performance of SANR_CNN in a few existing models in regard with peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The proposed SANR_CNN model achieved higher PSNR, SSIM, and MSE efficiency than the other noise removal techniques. The proposed architecture also provides transmission of these denoised medical images through secured IoT architecture. 相似文献
4.
Salvador Calderon-Uribe;Luis A. Morales-Hernandez;Jose O. De Leo-Jimenez;Emmanuel Resendiz-Ochoa;Manuel Toledano-Ayala;Irving A. Cruz-Albarran; 《International journal of imaging systems and technology》2024,34(3):e23074
Magnetic resonance imaging is an essential tool for the identification of neurological problems since it provides relevant information on brain development. The aim of the present work was the detection of neurological alterations in newborns from 4 to 12 months of age by segmentation and analysis of lateral ventricles in magnetic resonance images. For this purpose, an automated deep approach based on U-net is proposed to segment the cerebral ventricles of the newborn. Subsequently, for these regions, features were extracted based on the patient's clinical history and on the shape (area, roundness, normalized central moment, among others) and pixel intensity (mean gray value, contrast level, among others). Once the features were extracted, different types of intelligent models (Logistic Regression, k-Nearest Neighbors (kNN), and a Convolutional Neural Network) were assessed to detect the presence of neurological alterations. The segmentation phase of the system was tested on 50 patients and the classification phase on 28 patients (11 healthy, 17 with neurological changes). The results show a DICE similarity coefficient of 0.89 and a volume ratio of 1.05 for the segmentation stage and an accuracy of 98%, precision of 100%, sensitivity of 92%, and specificity of 100% for the classification stage using kNN. The last one proved to be the most computationally feasible model, due to the time required for training and inference (0.36 s and 35.2e-4 s, respectively), as well as the consumption of computational resources (0.1 GB RAM CPU). In conclusion, it is possible to detect neurological alterations in newborns aged 4 to 12 months by segmenting and classifying the lateral ventricles in magnetic resonance images, using image processing techniques, the U-net, as well as the kNN algorithm. This proposed methodology could play an important role in the early diagnosis and treatment of neurological disorders. 相似文献
5.
Kiran Thapaliya Goo‐Rak Kwon 《International journal of imaging systems and technology》2014,24(4):284-292
In this article, a novel method is proposed for the detection of brain tumor in magnetic resonance images (MRIs). The features of Zernike moments are used to analyze the MRIs. The image is divided into two parts from the center of the image based on the average value of the pixel located at the center boundary, and new image vectors are formed to extract the tumor. The local statistics values obtained from the low and high order Zernike moments are used to calculate the appropriate threshold value for efficient tumor extraction. The proposed method successfully analyzes the tumor part of the image on testing with different MRIs. 相似文献
6.
现有核磁共振设备面对主磁场不均匀多是采取贴磁片等补偿磁场不均匀等硬件方法,但这给成像带来图像伪影,图像模糊等不良影响。针对磁共振成像中磁场不均匀的问题,提出了一种主磁场不均匀下的分数域磁共振成像方法。首先选择待成像活体组织的某一层,在该层上选择若干个点,测量该层面上的磁场强度大小,在磁共振成像原理的基础上,建立成像区域磁场强度分布模型,然后建立磁场的多项式模型,按照测量的磁场中是否存在明显的二阶分量可以将该多项式模型分为二阶多项式模型和高阶多项式模型;之后,将这两个模型分别代入磁共振的自由感应衰减(FID)信号中,对于二阶模型可以用分数阶傅里叶变换工具进行求解成像物体某一层上的自旋密度函数,对于高阶模型需要通过求解代数方程的方法得到成像物体某一层面上的自旋密度函数,这样便建立了主磁场任意不均匀下的磁共振信号模型。实验结果表明,该方法达到与均匀主磁场下近似同样的效果。 相似文献
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Padma Ganasala Achanta Durga Prasad 《International journal of imaging systems and technology》2020,30(3):544-557
Medical image fusion is widely used in various clinical procedures for the precise diagnosis of a disease. Image fusion procedures are used to assist real-time image-guided surgery. These procedures demand more accuracy and less computational complexity in modern diagnostics. Through the present work, we proposed a novel image fusion method based on stationary wavelet transform (SWT) and texture energy measures (TEMs) to address poor contrast and high-computational complexity issues of fusion outcomes. SWT extracts approximate and detail information of source images. TEMs have the capability to capture various features of the image. These are considered for fusion of approximate information. In addition, the morphological operations are used to refine the fusion process. Datasets consisting of images of seven patients suffering from neurological disorders are used in this study. Quantitative comparison of fusion results with visual information fidelity-based image fusion quality metric, ratio of spatial frequency error, edge information-based image fusion quality metric, and structural similarity index-based image fusion quality metrics proved the superiority. Also, the proposed method is superior in terms of average execution time to state-of-the-art image fusion methods. The proposed work can be extended for fusion of other imaging modalities like fusion of functional image with an anatomical image. Suitability of the fused images by the proposed method for image analysis tasks needs to be studied. 相似文献
9.
Cheng Zhang Li Li Felicity Y. Han Xinying Yu Xiao Tan Changkui Fu Zhi Ping Xu Andrew K. Whittaker 《Small (Weinheim an der Bergstrasse, Germany)》2019,15(36)
19F magnetic resonance imaging (19F MRI) agents capable of being activated upon interactions with cancer triggers are attracting increasing attention, although challenges still remain for precise and specific detection of cancer tissues. In this study, a novel hybrid 19F MRI agent for pH‐sensitive detection of breast cancer tissues is reported, a composite system designed by conjugating a perfluoropolyether onto the surface of manganese‐incorporated layered double hydroxide (Mn‐LDH@PFPE) nanoparticles. The 19F NMR/MRI signals from aqueous solutions of Mn‐LDH@PFPE nanoparticles are quenched at pH 7.4, but “turned on” following a reduction in pH to below 6.5. This is due to partial dissolution of Mn2+ from the Mn‐LDH nanoparticles and subsequent reduction in the effect of paramagnetic relaxation. Significantly, in vivo experiments reveal that an intense 19F MR signal can be detected only in the breast tumor tissue after intravenous injection of Mn‐LDH@PFPE nanoparticles due to such a specific activation. Thus pH‐activated Mn‐LDH@PFPE nanoparticles are a potential “smart” 19F MRI agent for precise and specific detection of cancer diseases. 相似文献
10.
Y. Feng T. M. Abney R. J. Okamoto R. B. Pless G. M. Genin P. V. Bayly 《Journal of the Royal Society Interface》2010,7(53):1677-1688
This study describes the measurement of fields of relative displacement between the brain and the skull in vivo by tagged magnetic resonance imaging and digital image analysis. Motion of the brain relative to the skull occurs during normal activity, but if the head undergoes high accelerations, the resulting large and rapid deformation of neuronal and axonal tissue can lead to long-term disability or death. Mathematical modelling and computer simulation of acceleration-induced traumatic brain injury promise to illuminate the mechanisms of axonal and neuronal pathology, but numerical studies require knowledge of boundary conditions at the brain–skull interface, material properties and experimental data for validation. The current study provides a dense set of displacement measurements in the human brain during mild frontal skull impact constrained to the sagittal plane. Although head motion is dominated by translation, these data show that the brain rotates relative to the skull. For these mild events, characterized by linear decelerations near 1.5g (g = 9.81 m s−2) and angular accelerations of 120–140 rad s−2, relative brain–skull displacements of 2–3 mm are typical; regions of smaller displacements reflect the tethering effects of brain–skull connections. Strain fields exhibit significant areas with maximal principal strains of 5 per cent or greater. These displacement and strain fields illuminate the skull–brain boundary conditions, and can be used to validate simulations of brain biomechanics. 相似文献
11.
Jayesh P. Thawani Ahmad Amirshaghaghi Lesan Yan Joel M. Stein Jessica Liu Andrew Tsourkas 《Small (Weinheim an der Bergstrasse, Germany)》2017,13(37)
A common cause of local tumor recurrence in brain tumor surgery results from incomplete surgical resection. Adjunctive technologies meant to facilitate gross total resection have had limited efficacy to date. Contrast agents used to delineate tumors preoperatively cannot be easily or accurately used in the real‐time operative setting. Although multimodal imaging contrast agents are developed to help the surgeon discern tumor from normal tissue in the operating room, these contrast agents are not readily translatable. This study has developed a novel contrast agent comprised solely of two Food and Drug Administration approved components, indocyanine green (ICG) and superparamagnetic iron oxide (SPIO) nanoparticles—with no additional amphiphiles or carrier materials, to enable preoperative detection by magnetic resonance (MR) imaging and intraoperative photoacoustic (PA) imaging. The encapsulation efficiency of both ICG and SPIO within the formulated clusters is ≈100%, and the total ICG payload is 20–30% of the total weight (ICG + SPIO). The ICG–SPIO clusters are stable in physiologic conditions; can be taken up within tumors by enhanced permeability and retention; and are detectable by MR. In a preclinical surgical resection model in mice, following injection of ICG–SPIO clusters, animals undergoing PA‐guided surgery demonstrate increased progression‐free survival compared to animals undergoing microscopic surgery. 相似文献
12.
Aruna Devi Balasubramanian Pallikonda Rajasekaran Murugan Arun Prasath Thiyagarajan 《International journal of imaging systems and technology》2019,29(4):399-418
Computer-aided diagnosis (CAD) is a computerized way of detecting tumors in MR images. Magnetic resonance imaging (MRI) has been generally used in the diagnosis and detection of pancreatic tumors. In a medical imaging system, soft tissue contrast and noninvasiveness are clear preferences of MRI. Inaccurate detection of tumor and long time consumption are the disadvantages of MRI. Computerized classifiers can greatly renew the diagnosis activity, in terms of both accuracy and time necessity by normal and abnormal images, automatically. This article presents an intelligent, automatic, accurate, and robust method to classify human pancreas MRI images as normal or abnormal in terms of pancreatic tumor. It represents the response of artificial neural network (ANN) and support vector machine (SVM) techniques for pancreatic tumor classification. For this, we extract features from MR images of pancreas using the GLCM method and select the best features using JAFER algorithm. These features are analyzed by five classification techniques: ANN BP, ANN RBF, SVM Linear, SVM Poly, and SVM RBF. We compare the results with benchmark data set of MR brain images. The analytical outcome presents that the two best features used to classify the MR images using ANN BP technique have 98% classification accuracy. 相似文献
13.
为确保医用磁共振成像系统的影像质量,采用美国模体实验室和Goodenough博士研制的magphan模体,根据美国医学物理学家协会(AAPM)的建议和美国电气制造商协会(NEMA)提出的标准方法,对影响图像质量的信噪比、均匀性、空间分辨率、密度分辨率、线性、层厚及纵横比等主要性能参数进行检测。结果表明,上述的国外标准比较符合我国的实际情况,测量结果能够比较全面地评价医用磁共振成像系统的各项性能参数,为医生准确诊断病情提供可靠保障。 相似文献
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Dong‐Hoon Lee Cheol‐Pyo Hong Man‐Woo Lee Bong‐Soo Han 《International journal of imaging systems and technology》2013,23(4):289-293
The image quality of fast spin echo (FSE) is more sensitive than the typical spin echo pulse sequence caused by the eddy current effect. Microsecond‐scale misalignment of primary spin echoes produces a large spatial variation in image signal intensity. In this study, we describe an auto prescan calibration method that can improve the FSE image quality and minimize the eddy current effect on the image. We used a 0.32 T MRI system and obtained phantom and lumbar images. For FSE image correction, the optimal ranges and steps were determined to find the appropriate values, which were added to or subtracted from the gradient area values for each slice. The appropriate value of each slice could be found using the maximum signal intensity when the refocusing gradient area was changed by a number of steps in the optimal range. The determined value of each slice was applied before each slice image acquisition. The determined optimal step numbers and ranges were applied to in vivo image acquisition, and confirmed the reconstructed image quality. Based on our results, the obtained phantom and lumbar images were shown to be well corrected. The corrected images represented the image quality improvement and elimination of ghosting and blurring artifacts. In conclusion, we have proposed an FSE correction technique that automatically adjusts slice selection for the refocusing gradient balance during prescan, and confirmed that the calibration technique is very reliable even within complex in vivo images. We believe that our proposed technique will greatly benefit in MRI systems. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 289–293, 2013 相似文献
16.
In medicine,discrimination between pathologies and normal areas is of great importance,and in most cases,such discrimination is made possible by novel imaging technologies.Numerous modalities have been developed to visualize tissue vascularization in cardiovascular diseases or during angiogenic and vasculogenic processes.Here,we report the recent advances in vasculature imaging,providing an overview of the current non-invasive approaches in biomedical diagnostics and potential future strategies for prognostic assessment of vessel diseases,such as aneurysms and coronary artery occlusion leading to myocardial infarction.There are several contrast agents (CAs) available to improve the visibility of specific tissues at the early stage of diseases,allowing for rapid treatment.However,CAs are also hampered by numerous limitations,including rapid diffusion from blood vessels into the interstitial space,toxicity,and low sensitivity.Extravasation from blood vessels leads to a rapid loss of the image.If the contrast medium can fully be confined to the vascular space,high-resolution structural and functional vascular imaging could be obtained.Many scientists have contributed new materials and/or new carrier systems.For example,the use of red blood cells (RBCs) as CA-delivery systems appears to provide a scalable alternative to current procedures that allows adequate vascular imaging.Recognition and removal of CAs from the circulation can be prevented and/or delayed by using RBCs as biomimetic CA-carriers,and this technology should be clinically validated. 相似文献
17.
Carlo Ciulla Ustijana Rechkoska Shikoska Dimitar Veljanovski Filip A. Risteski 《International journal of imaging systems and technology》2018,28(1):54-63
The intensity‐curvature functional (ICF) of a model polynomial function is defined on a pixel‐by‐pixel basis by the ratio between the intensity‐curvature term before interpolation and the intensity‐curvature term after interpolation. Through the comparison with the traditional high‐pass filter (HPF), this work presents evidence that the ICFs of three model polynomial functions can be tuned as HPFs. The evidence consists of the mathematical characterization of the ICF‐based HPFs, qualitative comparisons in magnetic resonance imaging (MRI) of the human brain, and the determination of the finite impulse response (FIR) of the filters. The ICF‐based HPFs can remove periodic noise in the low‐frequency band. 相似文献
18.
Xihui Gao Qi Yue Zining Liu Mengjing Ke Xingyu Zhou Sihan Li Jianping Zhang Ren Zhang Liang Chen Ying Mao Cong Li 《Advanced materials (Deerfield Beach, Fla.)》2017,29(21)
Surgical resection is a mainstay in the treatment of malignant brain tumors. Surgeons, however, face great challenges in distinguishing tumor margins due to their infiltrated nature. Here, a pair of gold nanoprobes that enter a brain tumor by crossing the blood–brain barrier is developed. The acidic tumor environment triggers their assembly with the concomitant activation of both magnetic resonance (MR) and surface‐enhanced resonance Raman spectroscopy (SERRS) signals. While the bulky aggregates continuously trap into the tumor interstitium, the intact nanoprobes in normal brain tissue can be transported back into the blood stream in a timely manner. Experimental results show that physiological acidity triggers nanoparticle assembly by forming 3D spherical nanoclusters with remarkable MR and SERRS signal enhancements. The nanoprobes not only preoperatively define orthotopic glioblastoma xenografts by magnetic resonance imaging (MRI) with high sensitivity and durability in vivo, but also intraoperatively guide tumor excision with the assistance of a handheld Raman scanner. Microscopy studies verify the precisely demarcated tumor margin marked by the assembled nanoprobes. Taking advantage of the nanoprobes' rapid excretion rate and the extracellular acidification as a hallmark of solid tumors, these nanoprobes are promising in improving brain‐tumor surgical outcome with high specificity, safety, and universality. 相似文献
19.
P. Eben Sophia J. Anitha 《International journal of imaging systems and technology》2017,27(2):171-181
Contextual compression is an essential part of any medical image compression since it facilitates no loss of diagnostic information. Although there are many techniques available for contextual image compression still there is a need for developing an efficient and optimized technique which would produce good quality images at lower bit rates. This article presents an efficient contextual compression algorithm using wavelet and contourlet transforms to capture the fine details of the image, along with directional information to produce good quality at high Compression Ratio (CR). The 2D discrete wavelet transform, which uses the simplest Daubechies wavelets, db1, or haar wavelet, is chosen and used to get the subband coefficients. The approximate coefficients of the higher subbands undergo contourlet transform employing length N ladder filters for capturing the directional information of the subbands at different scale and orientations. An optimized approach is used for predicting the quantized and the normalized subband coefficients resulting in improved compression performance. The proposed contextual compression approach was evaluated for its performance in terms of CR, Peak Signal to Noise Ratio, Feature SIMilarity index, Structure SIMilarity Index, and Universal quality (Q) after reconstruction. The results clarify the efficiency of the proposed method over other compression techniques. 相似文献
20.
A. Jayachandran R. Dhanasekaran 《International journal of imaging systems and technology》2013,23(2):97-103
Segmentation is the process of labeling objects in image data. It is a decisive phase in several medical imaging processing tasks for operation planning, radio therapy or diagnostics, and widely useful for studying the differences of healthy persons and persons with tumor. Magnetic Resonance Imaging brain tumor segmentation is a complicated task due to the variance and intricacy of tumors. In this article, a tumor segmentation scheme is presented, which focuses on the structural analysis on both tumorous and normal tissues. Our proposed method hits the target with the aid of the following major steps: (i) Tumor Region Location, (ii) Feature Extraction using Multi‐texton Technique, and (iii) Final Classification using support vector machine (SVM). The results for the tumor detection are validated through evaluation metrics such as, sensitivity, specificity, and accuracy. The comparative analysis is carried out by Radial Basis Function neural network and Feed Forward Neural Network. The obtained results depict that the proposed Multi‐texton histogram and support vector machine based brain tumor detection approach is more robust than the other classifiers in terms of sensitivity, specificity, and accuracy. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 97–103, 2013 相似文献