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Int. J. Medical Eng. Informatics最新文献

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Breast cancer detection in mammogram image with segmentation of tumour region 基于肿瘤区域分割的乳房x线图像乳腺癌检测
Int. J. Medical Eng. Informatics Pub Date : 2020-03-06 DOI: 10.1504/ijmei.2020.10027430
Vikramathithan A C, D. Shashikumar
{"title":"Breast cancer detection in mammogram image with segmentation of tumour region","authors":"Vikramathithan A C, D. Shashikumar","doi":"10.1504/ijmei.2020.10027430","DOIUrl":"https://doi.org/10.1504/ijmei.2020.10027430","url":null,"abstract":"In our proposed breast cancer malignant detection study are performed with the aid of fuzzy min max neural network technique. Majority of women's are affected in this breast cancer at a early stage the mammogram images are mostly play in a vital role. Initially the input mammogram image smoothened with the aid of adaptive median filer from that smoothened image we are segmenting tissues with the aid of Histon based fuzzy c-means clustering. We are extracting features from that segmented image the features are statistical and semantic features. Then we can identify the malignant region with the aid of these features. The segmented region is maligned or benign using an optimal fuzzy min max neural network with grey wolf optimisation algorithm with the aid of these we will identify a breast cancer region.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124528124","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: 5
Optimised DBN for effective enhancement of ultrasound images with pelvic lesions 优化DBN有效增强超声图像与盆腔病变
Int. J. Medical Eng. Informatics Pub Date : 2019-08-14 DOI: 10.1504/IJMEI.2019.10023200
Sadanand L. Shelgaonkar, A. Nandgaonkar
{"title":"Optimised DBN for effective enhancement of ultrasound images with pelvic lesions","authors":"Sadanand L. Shelgaonkar, A. Nandgaonkar","doi":"10.1504/IJMEI.2019.10023200","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10023200","url":null,"abstract":"Nowadays, the ultrasound modality is the current research areas for lesion analysis. Hence, this paper adopts an optimised deep belief neural (ODBN) network for enhancing the US image of pelvic portions. It considers the higher order and lower order statistical characteristics of the image to define the appropriate filter band for image enhancement. To optimise the lower order features, an advanced optimisation search algorithm named grey wolf optimiser algorithm (GWO) is exploited. The ODBN learns the optimised features and the noise characteristics for precise prediction of the filter bands, which enhance the image substantially over the conventional filter bands. The performance of the proposed method is compared with the conventional methods using the benchmark and real-time US images of pelvic lesions. The quality of enhancement is ensured using renowned measures namely PSNR and ESSIM that exhibit the performance of the proposed approach.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128670392","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
An innovative technical solution to avoid insomnia and noise-induced hearing loss 一个创新的技术解决方案，以避免失眠和噪音引起的听力损失
Int. J. Medical Eng. Informatics Pub Date : 2019-08-14 DOI: 10.1504/IJMEI.2019.10023201
S. K. Vasudevan, Ikram Shah, Sriharsha Patallapalli, S. Karthikeyan, S. Chandran, U. A. Bharadwaj
{"title":"An innovative technical solution to avoid insomnia and noise-induced hearing loss","authors":"S. K. Vasudevan, Ikram Shah, Sriharsha Patallapalli, S. Karthikeyan, S. Chandran, U. A. Bharadwaj","doi":"10.1504/IJMEI.2019.10023201","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10023201","url":null,"abstract":"The major challenge these days with the increased usage of the mobile phone is loss of sleep, and threat to mental wellness. Sleep time is meant for the brain to rejuvenate. If the sleep patterns are disturbed due to a continuous external disturbance, it is most likely to disturb the deep sleep. It is wise to switch-off the music after the person sleeps which most of us do not do as we are already slept by then. Many researches convey that music is a solution to reduce stress and to bring sleep. But, we are using headphones for music and it causes side-effects including affecting sleep and noise induced hearing loss (NIHL). Here, we propose a system which will ensure that the music player is stopped after understanding that the person using it has slept and he no more needs the tunes thereby not disturbing the sleep and preventing insomnia/NIHL.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114717784","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
Product unit neural network trained by an evolutionary algorithm for diabetes disease diagnosis 基于进化算法训练的产品单元神经网络用于糖尿病疾病诊断
Int. J. Medical Eng. Informatics Pub Date : 2019-08-14 DOI: 10.1504/IJMEI.2019.10023202
R. Benali, Dib Nabil, F. Bereksi-Reguig
{"title":"Product unit neural network trained by an evolutionary algorithm for diabetes disease diagnosis","authors":"R. Benali, Dib Nabil, F. Bereksi-Reguig","doi":"10.1504/IJMEI.2019.10023202","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10023202","url":null,"abstract":"Diabetes disease occurs when the level of glucose in the blood becomes higher than normal because the body is unable to produce the insulin which is needed to regulate glucose. In this study, a new classification method for the diagnosis of diabetes disease was developed. This method is based on a special class of neural network known as product-unit neural networks (PUNN) which was trained by an evolutionary algorithm (EA). We have used EA in order to determine the basic topology of the structure of the PUNN, and to estimate its coefficients weights. The performances of the proposed classifier were evaluated through the sensitivity, the specificity and the classification accuracy using both conventional and 10-fold cross-validation method using the Pima Indian diabetes (PID) dataset. Obtained results reveal that the proposed approach outperforms several famous and recent methods existing in the literature for diabetes disease diagnosis.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125613750","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
Learn quest - a virtual reality based system for training autistic kids 学习任务-一个基于虚拟现实的训练自闭症儿童的系统
Int. J. Medical Eng. Informatics Pub Date : 2019-01-30 DOI: 10.1504/IJMEI.2019.10018831
S. K. Vasudevan, S. Abhishek, S. Swathi, A. Lakshmi, S. Anandaram
{"title":"Learn quest - a virtual reality based system for training autistic kids","authors":"S. K. Vasudevan, S. Abhishek, S. Swathi, A. Lakshmi, S. Anandaram","doi":"10.1504/IJMEI.2019.10018831","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10018831","url":null,"abstract":"Childhood is the best part of life. A child enjoys anything and everything in this world without any discriminations. It is also the period of rapid brain development, where the kids learn the stepping stones for life. Autism spectrum disorder (ASD) is a group of developmental disabilities that causes major impairments in social, communication and behavioural aspects of the children. Unlike other children, an autistic kid finds it difficult to go along and communicate with others. Social interactions and communication are the major aspects for peaceful living of any human being, and these children face difficulties in the same. So, we have developed a virtual reality based game engine that would attract the children and make them enjoy interacting with it while increasing the chance for learning. As the children continues playing this game, their learning and interacting ability increases nullifying some effects of autism, thus making it a boon for these kids.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126237064","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
Generating a stable primary schedule for an integrated surgical suite 为综合手术组制定稳定的主要时间表
Int. J. Medical Eng. Informatics Pub Date : 2019-01-29 DOI: 10.1504/IJMEI.2019.10018838
A. Soudi, M. Heydari
{"title":"Generating a stable primary schedule for an integrated surgical suite","authors":"A. Soudi, M. Heydari","doi":"10.1504/IJMEI.2019.10018838","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10018838","url":null,"abstract":"Efficient utilisation of operating room (OR) is a common anxiety of surgical suit manager which necessitate an effective planning and scheduling of surgeries. In this paper we investigate predictive/reactive scheduling of an integrated surgical suite in the form of a two-stage hybrid flow shop scheduling problem (HFSP). The deterministic model comprises both assignment and sequencing decisions for elective surgeries. By further considering shared capacity between elective and emergency patients, a chance constrained programming model is extended for the first time to cope with uncertain disruption. It is shown that how a chance constrained model will reduce to just considering an augmented surgery which processing time depends on distribution function of emergency surgery processing time and confidence level of scheduler. Two new important measures in reactive scheduling literature, 'stability' and 'robustness' are taking into account in surgical suite scheduling for the first time. Computational results demonstrate the efficiency of primary schedule generated by extended chance constrained programming model as well as the effectiveness of new measures in hospitals. As the chance constrained model is NP-hard, a decomposition heuristic algorithm based on tabu search (TS) is proposed to cope with problems of real size.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132804549","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
Spectro-temporal analysis of electromyogram signals 肌电信号的光谱-时间分析
Int. J. Medical Eng. Informatics Pub Date : 2019-01-29 DOI: 10.1504/ijmei.2019.10018837
F. Meziani, S. Rerbal, Debbal Sidi Mouhamed
{"title":"Spectro-temporal analysis of electromyogram signals","authors":"F. Meziani, S. Rerbal, Debbal Sidi Mouhamed","doi":"10.1504/ijmei.2019.10018837","DOIUrl":"https://doi.org/10.1504/ijmei.2019.10018837","url":null,"abstract":"Electromyography (EMG) signals can be used for clinical/biomedical applications, that measures electrical currents generated in muscles during its contraction representing neuromuscular. Individual muscle fibre action potentials are sometimes acquired using wire or needle electrodes placed directly in the muscle (invasive) or by a surface electrode (non-invasive). The combination of the muscle fibre action potentials from all the muscle fibres of a single motor unit is the motor unit action potential (MUAP). The simple detection with electrodes is insufficient to diagnose some neuromuscular diseases. The efficiency of diagnosis can be improved considerably by using modern signal processing techniques. The aim of this study is to analyse EMGs signals using temporal and frequency analysis. This analysis can provide a wide range of information's related to the type of signal (normal and pathological).","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131301648","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
Health panel: a platform useful to physicians for fast and easy managing of FPGA-based medical devices 健康面板:一个对医生有用的平台，可以快速轻松地管理基于fpga的医疗设备
Int. J. Medical Eng. Informatics Pub Date : 2019-01-29 DOI: 10.1504/IJMEI.2019.10018836
A. Giorgio
{"title":"Health panel: a platform useful to physicians for fast and easy managing of FPGA-based medical devices","authors":"A. Giorgio","doi":"10.1504/IJMEI.2019.10018836","DOIUrl":"https://doi.org/10.1504/IJMEI.2019.10018836","url":null,"abstract":"The design of medical devices is frequently based on field programmable gate arrays (FPGAs). This is especially due to their unique properties in order to fast prototyping and their great capabilities in digital signal processing (DSP). The problem arises to make physicians able to manage such devices especially to set and program during prototyping, experimental and validation processes of new medical devices. Therefore, the objective of this paper is the description of a platform, named health panel, in its hardware and software components, overcoming these issues. The design methods and the test and debug methods are also detailed. The hardware is an embedded system (ES) and the software, developed in MATLAB environment, acts as user friendly interface making the physician able to manage quick and easy the FPGA. Results of tests and of an accurate debug of the platform are described. The platform aims at providing a significance contribution for designing hardware and software interfaces for an easy and quick use of FPGA-based medical devices. Conclusions and final remarks provide suggestions for future developments of the platform.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116578180","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
Hard exudate based severity assessment of diabetic macular edema from retinal fundus images 视网膜眼底图像中基于硬渗出物的糖尿病性黄斑水肿严重程度评估
Int. J. Medical Eng. Informatics Pub Date : 2018-10-04 DOI: 10.1504/IJMEI.2018.10014082
D. K. Prasad, L. Vibha, K. Venugopal
{"title":"Hard exudate based severity assessment of diabetic macular edema from retinal fundus images","authors":"D. K. Prasad, L. Vibha, K. Venugopal","doi":"10.1504/IJMEI.2018.10014082","DOIUrl":"https://doi.org/10.1504/IJMEI.2018.10014082","url":null,"abstract":"Diabetic macular edema (DME) is a consequence of diabetic retinopathy characterised by the abnormal accumulation of fluid and protein deposit in the macula region of the retina. Prior disclosure of even a trivial trace of DME is essential as it could consequently lead to blurred vision. DME can be diagnosed by the presence of exudates (glossy lesions) in the retinal fundus images. In this work, OD and macula are detected using morphological operation and hard exudates are segmented. Exudates are classified using early treatment diabetic retinopathy standard as normal, moderate or severe cases. The proposed work also incorporates the extraction of various features from the retinal fundus image. Various textural and exudate features are extracted and fed to a classifier to detect DME. Experiments are performed on a publically available database. Performance is evaluated with metrics like accuracy, sensitivity, specificity and accuracy. The results obtained are promising.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128973125","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
Breast abnormality based early diagnosis of breast cancer using non-invasive digital infrared thermal imaging 基于乳腺异常的无创数字红外热成像早期诊断乳腺癌
Int. J. Medical Eng. Informatics Pub Date : 2018-10-04 DOI: 10.1504/IJMEI.2018.10014081
Priyanka Hankare
{"title":"Breast abnormality based early diagnosis of breast cancer using non-invasive digital infrared thermal imaging","authors":"Priyanka Hankare","doi":"10.1504/IJMEI.2018.10014081","DOIUrl":"https://doi.org/10.1504/IJMEI.2018.10014081","url":null,"abstract":"Breast cancer is one of the most leading and common cause of cancer. It can be detected by infrared thermal imaging Technique by observing the temperature distribution on the breast. Breast thermography is considered as a valuable tool for early breast tumours detection. The fast growing tumour has a higher metabolic rate and associated increase in local vascularisation. It will cause the occurrence of some asymmetric heat patterns. Clinical interpretation of a breast thermogram can be done on the asymmetry analysis of the heat patterns visually and subjectively. In this paper, a new approach for early detection of breast cancer is proposed using asymmetry analysis of breast thermograms. The heat patterns are segmented and the asymmetry analysis is performed by using histogram generation and feature extraction. Extracted statical features clearly indicate the abnormality of a breast thermogram.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123672006","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
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