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Int. J. Medical Eng. Informatics最新文献

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Novel multiphase contouring and force calculation algorithm for ROI detection and calculation of energy value in multiple scale and orientation for early detection of stages of breast cancer 基于ROI检测的新型多相轮廓力计算算法及多尺度、多方位的能量值计算，用于乳腺癌早期检测
Int. J. Medical Eng. Informatics Pub Date : 2020-05-07 DOI: 10.1504/IJMEI.2020.10020510
M. Varalatchoumy, M. Ravishankar
{"title":"Novel multiphase contouring and force calculation algorithm for ROI detection and calculation of energy value in multiple scale and orientation for early detection of stages of breast cancer","authors":"M. Varalatchoumy, M. Ravishankar","doi":"10.1504/IJMEI.2020.10020510","DOIUrl":"https://doi.org/10.1504/IJMEI.2020.10020510","url":null,"abstract":"A novel MCFC algorithm has been developed to perform detection of ROI. Detected malignant tumors were processed using a novel approach to identify stages of breast cancer. Preprocessing phase aids in enhancement and noise removal. Preprocessed image is segmented using the MCFC algorithm to detect the ROI that aided in achieving robust segmentation at very low computation time. Combination of wavelet and textural features were used to train the artificial neural network for classification. Tumour stage is identified using a novel approach of calculating the energy values in four different scales and six orientations for each scale. Total of 24 energy values are used for training. System performance was tested on 45 real time patients mammographic images obtained from hospitals. Detection of malignant tumour and its stages was verified by experts in medical field. Overall accuracy obtained is 97% for MIAS images and 90% for real time mammographic images.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125023918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimised feature selection and entropy-based graph classification of gene expression data 基因表达数据的优化特征选择与熵图分类
Int. J. Medical Eng. Informatics Pub Date : 2020-05-07 DOI: 10.1504/ijmei.2020.10029320
A. Mabu, R. Prasad, Raghav Yadav
{"title":"Optimised feature selection and entropy-based graph classification of gene expression data","authors":"A. Mabu, R. Prasad, Raghav Yadav","doi":"10.1504/ijmei.2020.10029320","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10029320","url":null,"abstract":"Gene expression (GE) profiles expansively revised to disclose intuition into the multifariousness of cancer furthermore to discover concealed information which provides biological knowledge for the classification of cancer. Precise cancer classification straightly through original GE profiles stays challenging on account of the intrinsic high-dimension feature along with the small magnitude of the data samples. Therefore, choosing high discriminative genes as of the GE data have turn into progressively fascinating in the bioinformatics field. This given paper gives a technique for the GE data classification utilising entropy-based graph classifier. Initially, the proposed technique evaluate the GE data's signal to noise ratio (SNR) values, additionally, selects the relevant features using krill herd (KH) optimization process. The truth is that not all features are helpful for classification, and some redundant together with the irrelevant features might even serve as outlier. To dispose the outliers, feature reduction is done with the assist of Euclidean distance. Classification is made utilising entropy-based graph classifier. The proposed process' effectiveness contrasted with the existing method concerning classifications is established from the experimental outcome.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124968936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Wavelet packet transform-based medical image multiple watermarking with independent component analysis extraction 基于小波包变换的医学图像多重水印独立分量分析提取
Int. J. Medical Eng. Informatics Pub Date : 2020-05-07 DOI: 10.1504/ijmei.2020.10029318
N. Rajendiran, Thirugnanam Gurunathan, M. Palanivel
{"title":"Wavelet packet transform-based medical image multiple watermarking with independent component analysis extraction","authors":"N. Rajendiran, Thirugnanam Gurunathan, M. Palanivel","doi":"10.1504/ijmei.2020.10029318","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10029318","url":null,"abstract":"Rapid growth of internet in all aspects of life has led to the easy availability of the digital data to everyone. E-commerce, telemedicine, etc., are among the many applications of internet. Telemedicine is a crucial field where internet finds application. Healthcare professionals use internet to transmit and receive medical data. Thus the medical images can be shared, processed and transmitted through computer networks. All patient records, linked to the medical secrecy, must be confidential. Because of the importance of the security issues in the management of medical information, there is a need to develop watermarking techniques for protecting medical images. In this paper, colour medical image watermarking methods rely on wavelet packet transform (WPT) and extraction using independent component analysis (ICA). For watermark extraction, Pearson ICA is applied as it attains the new trait is that it not entail the renovation procedure in watermark extraction. The grades show that projected method is vigorous beside attacks such as Gaussian noise, salt and pepper noise, rotation and translation. The performance measures like PSNR, similarity measure and normalised correlation are assessed to confirm the robustness of the scheme.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"129 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128324806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Study of murmurs and their impact on the heart variability 杂音及其对心脏变异性影响的研究
Int. J. Medical Eng. Informatics Pub Date : 2020-04-24 DOI: 10.1504/ijmei.2020.10028849
F. Mokeddem, F. Meziani, Debbal Sidi Mouhamed
{"title":"Study of murmurs and their impact on the heart variability","authors":"F. Mokeddem, F. Meziani, Debbal Sidi Mouhamed","doi":"10.1504/ijmei.2020.10028849","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028849","url":null,"abstract":"The phonocardiogram (PCG) signal processing approach seems to be very revealing for the diagnosis of pathologies affecting the activity of the heart. The aim of this paper is the application of an algorithm to explore heart sounds with simplicity in order to provide statistical parameters to better understand the cardiac activity by the calculation of the cardiac frequency and examine the impact of minor and pronounced murmurs on the cardiac variability. This paper is conducted to clarify the variation of the cardiac frequency affected by several groups of murmurs and investigate the medical reasons behind the obtained results. A high number of cycles were used to better refine the expected results.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127402141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Peak alpha neurofeedback training on cognitive performance in elderly subjects 峰值α神经反馈训练对老年受试者认知表现的影响
Int. J. Medical Eng. Informatics Pub Date : 2020-04-24 DOI: 10.1504/ijmei.2021.10022176
J. Bobby
{"title":"Peak alpha neurofeedback training on cognitive performance in elderly subjects","authors":"J. Bobby","doi":"10.1504/ijmei.2021.10022176","DOIUrl":"https://doi.org/10.1504/ijmei.2021.10022176","url":null,"abstract":"Slowing down of thought, memory and thinking is a normal part of aging. Neurofeedback training (NFT) is a relatively new biofeedback technique that focuses on helping a person train themselves to directly affect brain function. In this study, EEG signal was acquired using single channel electrode, amplified using EEG amplifier and connected to the system through data acquisition device (DAQ). The peak alpha band (10-11 Hz) signal was extracted using LabVIEW software. The NFT protocol that was designed presented the neurofeedback training and thereby showed some improvement in their cognitive processing speed. The visual cues were fed to the LabVIEW software by making the subject visualise some animation or hear some audios. Twenty subjects aged between 60 and 65 were considered for this training. This study had investigated whether the training given to the elderly people showed improvement in the cognitive processing speed of their brain activity.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125017682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A semantic interoperability framework for distributed electronic health record based on fuzzy ontology 基于模糊本体的分布式电子病历语义互操作框架
Int. J. Medical Eng. Informatics Pub Date : 2020-04-24 DOI: 10.1504/ijmei.2020.10028844
Ebtsam Adel, Shaker El-Sappagh, S. Barakat, Mohammed M Elmogy
{"title":"A semantic interoperability framework for distributed electronic health record based on fuzzy ontology","authors":"Ebtsam Adel, Shaker El-Sappagh, S. Barakat, Mohammed M Elmogy","doi":"10.1504/ijmei.2020.10028844","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028844","url":null,"abstract":"To achieve an efficient healthcare process; the professionals and doctors need to access the complete data about their patients in the suitable time. In the face of that issue; healthcare semantic interoperability is still a huge problem without solving. In this paper, a unified semantic interoperability framework for distributed EHR based on fuzzy ontology is proposed. The lowest layer stores the EHRs heterogeneous data with different models. In the middle layer, the local ontologies are mapped to a global crisp one. The global reference ontology combines and integrates all local ontologies and therefore describes all data. In the user interface layer, any linguistic or semantic queries can be done by dealing with only the global reference fuzzy ontology. We expect that our framework will handle the current EHR semantic interoperability challenges, reduce the cost of the integration process, and get a higher acceptance and accuracy rate than previous studies.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"417 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126700381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Modified model for cancer treatment 改良的癌症治疗模型
Int. J. Medical Eng. Informatics Pub Date : 2020-04-24 DOI: 10.1504/ijmei.2020.10028847
M. Shafigh
{"title":"Modified model for cancer treatment","authors":"M. Shafigh","doi":"10.1504/ijmei.2020.10028847","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028847","url":null,"abstract":"This paper proposes an optimal method for eradicating cancer, such that it cannot be relapsed. The major issue is that from the dynamical point of view, the tumour free equilibrium point at the end of chemotherapy is still unstable. Mathematically it means that when the chemotherapy is stopped, the dynamic behaviour of the system moves away from the tumour free equilibrium point and the tumour cells starts increasing. To overcome this problem, the stabilisation of the equilibrium point is proposed. According to this method, the vaccine therapy changes the dynamics of the system around the tumour free equilibrium point, and the chemotherapy pushes the system to the domain of attraction of the desired point. It is shown, that, according to the simulation results, after completing the chemotherapy process, the dynamic of the system becomes stable and the cancerous cells converges to zero.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122284265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Changes in scale-invariance property of electrocardiogram as a predictor of hypertension 心电图尺度不变性的变化作为高血压的预测指标
Int. J. Medical Eng. Informatics Pub Date : 2020-04-24 DOI: 10.1504/ijmei.2020.10028845
M. C. H. Mary, Dilbag Singh, K. Deepak
{"title":"Changes in scale-invariance property of electrocardiogram as a predictor of hypertension","authors":"M. C. H. Mary, Dilbag Singh, K. Deepak","doi":"10.1504/ijmei.2020.10028845","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028845","url":null,"abstract":"In this study, electrocardiogram signal has been investigated to assess the presence of scale-invariance changes to classify normotensive and hypertensive subject. ECG signal of 20 normotensive and 20 hypertensive subjects is recorded using MP100 system with a sampling rate (fs) of 500 Hz. The scale-invariance changes of ECG signal are analysed using multifractal detrended fluctuation analysis. The width and shape of the multifractal spectrum obtained is used to detect the hypertensive subject. The multifractal spectrum of the normotensive subject exhibit a pure Gaussian behaviour, but for hypertension subject is left truncated. The width of the multifractal spectrum for hypertension subject (1.7158 ± 0.09649) is more as compared to the normotensive subject (1.534 ± 0.23931). Therefore this method can reflect complexity changes of ECG signal during hypertension. Also, the changes in the multifractal behaviour of ECG signal improves the diagnostic tools for calculating hypertension and as a promising diagnostic tool in cardiovascular disease diagnosis and evaluation.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114453153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Malignant melanoma detection using multi layer preceptron with visually imperceptible features and PCA components from MED-NODE dataset 基于视觉难以察觉特征的多层感知器和MED-NODE数据集PCA成分的恶性黑色素瘤检测
Int. J. Medical Eng. Informatics Pub Date : 2020-04-21 DOI: 10.1504/ijmei.2020.10028644
Soumen Mukherjee, A. Adhikari, M. Roy
{"title":"Malignant melanoma detection using multi layer preceptron with visually imperceptible features and PCA components from MED-NODE dataset","authors":"Soumen Mukherjee, A. Adhikari, M. Roy","doi":"10.1504/ijmei.2020.10028644","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028644","url":null,"abstract":"In this paper, a scheme is worked out for classification of images belonging to malignant melanoma and nevus class by multi layer neural network architecture with different trainings and cost functions. Total 1,875 shape, colour and texture features are extracted from 170 images from MED-NODE dataset. With the total 1,875 features an accuracy of 82.05% is achieved. Feature ranking algorithm ReliefF is used for ranking these features. MLP is run with varying number of best ranked features. With 10 best features an accuracy of 83.33%, sensitivity of 86.77% and specificity of 72.78% are achieved with 3 fold cross-validation. Effect of pre-processing the features with principal component analysis is explored and found that the optimal number of principal components is 25, which yields a maximum accuracy of 87.18% which is much higher than the previously reported accuracy level with this dataset.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132696012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Enhancement and segmentation of histopathological images of cancer using dynamic stochastic resonance 动态随机共振对肿瘤组织病理图像的增强和分割
Int. J. Medical Eng. Informatics Pub Date : 2020-04-21 DOI: 10.1504/ijmei.2020.10028651
Anuranjeeta, Shiru Sharma, Neeraj Sharma, M. Singh, K. K. Shukla
{"title":"Enhancement and segmentation of histopathological images of cancer using dynamic stochastic resonance","authors":"Anuranjeeta, Shiru Sharma, Neeraj Sharma, M. Singh, K. K. Shukla","doi":"10.1504/ijmei.2020.10028651","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10028651","url":null,"abstract":"Pathologists face difficulty in cell image detection as uneven dye causes the low contrast and inhomogeneity. The proposed discrete cosine transform (DCT)-based dynamic stochastic resonance (DSR) technique enhances the histopathological images of cancer. Further, the DSR-based Otsu's thresholding processed image helps in the better segmentation of histopathological images of four types of cancer cells, i.e., breast, cervix, ovarian and prostate cancer. The comparison of segmentation results were performed on the University of California, Santabarbara (UCSB) available breast cancer datasets for analysis. The algorithm has been applied to total 22 breast cancer images including benign and malignant and compared with region of interest (ROI) segmented ground truth images to validate the performance of proposed DSR-based Otsu's thresholding. DSR-based Otsu's segmentation obtained better results with 0.776 average correlation, 0.979 average normalised probabilistic rand (NPR) index, 0.011 average global consistency error (GCE), and 0.185 average variation of information (VI). These indices are higher than the other conventional segmentation methods and have the advantage to identify the target objects in low contrast images.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132651829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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