Relevant bibliographies by topics / Biomedical analysis techniques

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biomedical analysis techniques'

Author: Grafiati
Published: 8 March 2025

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Journal articles on the topic "Biomedical analysis techniques"

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Kataoka, Hiroyuki. "SPME techniques for biomedical analysis." Bioanalysis 7, no. 17 (September 2015): 2135–44. http://dx.doi.org/10.4155/bio.15.145.

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Witte, H., and M. Wacker. "Time-frequency Techniques in Biomedical Signal Analysis." Methods of Information in Medicine 52, no. 04 (2013): 279–96. http://dx.doi.org/10.3414/me12-01-0083.

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SummaryObjectives: This review outlines the method -ological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications.Methods: The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT), and the Hilbert transform (HT) are introduced as linear transforms by using a unified concept of the time-frequency representation which is based on a standardized analytic signal. The Wigner-Ville dis -tribution (WVD) serves as an example of the ‘quadratic transforms’ class. The combination of WVD and GT with the matching pursuit (MP) decomposition and that of the HT with the empirical mode decomposition (EMD) are explained; these belong to the class of signal-adaptive approaches.Results: Similarities between linear transforms are demonstrated and differences with regard to the time-frequency resolution and interference (cross) terms are presented in detail. By means of simulated signals the effects of different time-frequency resolutions of the GT, CMWT, and WVD as well as the resolution-related properties of the inter -ference (cross) terms are shown. The method-inherent drawbacks and their consequences for the application of the time-frequency techniques are demonstrated by instantaneous amplitude, frequency and phase measures and related time-frequency representations (spectrogram, scalogram, time-frequency distribution, phase-locking maps) of measured magnetoencephalographic (MEG) signals.Conclusions: The appropriate selection of a method and its parameter settings will ensure readability of the time-frequency representations and reliability of results. When the time-frequency characteristics of a signal strongly correspond with the time-frequency resolution of the analysis then a method may be considered ‘optimal’. The MP-based signal-adaptive approaches are preferred as these provide an appropriate time-frequency resolution for all frequencies while simultaneously reducing interference (cross) terms.
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Malet-Martino, M., and U. Holzgrabe. "NMR techniques in biomedical and pharmaceutical analysis." Journal of Pharmaceutical and Biomedical Analysis 55, no. 1 (April 2011): 1–15. http://dx.doi.org/10.1016/j.jpba.2010.12.023.

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Szultka, Malgorzata, Pawel Pomastowski, Viorica Railean-Plugaru, and Boguslaw Buszewski. "Microextraction sample preparation techniques in biomedical analysis." Journal of Separation Science 37, no. 21 (September 25, 2014): 3094–105. http://dx.doi.org/10.1002/jssc.201400621.

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Kataoka, Hiroyuki, and Keita Saito. "Recent advances in SPME techniques in biomedical analysis." Journal of Pharmaceutical and Biomedical Analysis 54, no. 5 (April 2011): 926–50. http://dx.doi.org/10.1016/j.jpba.2010.12.010.

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Turnell, David C., and John D. H. Cooper. "Automation of liquid chromatographic techniques for biomedical analysis." Journal of Chromatography B: Biomedical Sciences and Applications 492 (August 1989): 59–83. http://dx.doi.org/10.1016/s0378-4347(00)84464-3.

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Cerutti, S. "On Time-frequency Techniques in Biomedical Signal Analysis." Methods of Information in Medicine 52, no. 04 (2013): 277–78. http://dx.doi.org/10.1055/s-0038-1627060.

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Abaid Mahdi, Muhammed, and Samaher Al_Janabi. "Evaluation prediction techniques to achieve optimal biomedical analysis." International Journal of Grid and Utility Computing 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijguc.2019.10020511.

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Scriba, Gerhard K. E. "Chiral electromigration techniques in pharmaceutical and biomedical analysis." Bioanalytical Reviews 3, no. 2-4 (September 27, 2011): 95–114. http://dx.doi.org/10.1007/s12566-011-0024-3.

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Kalish, Heather, and Terry Phillips. "The Application of Micro-Analytical Techniques to Biomedical Analysis." Current Pharmaceutical Analysis 5, no. 3 (August 1, 2009): 208–28. http://dx.doi.org/10.2174/157341209788922057.

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Dissertations / Theses on the topic "Biomedical analysis techniques"

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Esposito, Andrea. "Techniques of proteomic analysis as tools for studies in biomedical field." Doctoral thesis, Universita degli studi di Salerno, 2017. http://hdl.handle.net/10556/2487.

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2014 - 2015
It is known that prenatal exposure to pollutants and particularly heavy metals can have long term damaging consequences on infants, due to their accumulation in-body. Since the 1990s, ten million tonnes of waste have been illegally dumped in the area around Caserta and Naples. Thus, direct exposure to waste and heavy metals during the last two decades was very frequent in the so-called “Lands of fires”. The number of children suffering from cancer and of malformed fetuses in Italy's "Land of Fires", an area where toxic waste has been dumped by the mafia, is reported significantly higher than elsewhere in the country. In this thesis we examined the proteome of the umbilical cords from malformed fetuses obtained by therapeutic abortions, after mothers' being exposed to the pollution on “land of fire” during early pregnancy, and analyzed the differences between umbilical cords from malformed fetuses to healthy ones. The main goals were to understand the impact of the contamination by heavy metals on the fetus development, and to identify new putative biomarkers of exposure to metal contaminants. All umbilical cords were obtained in Campania region (Naples and Caserta, mainly in the “land of fires”). The collection of the biological samples was carried out in collaboration with the Caserta Hospital “Sant’Anna e San Sebastiano” and with the Avellino Hospital “San Giuseppe Moscati”. A proteomic approach based on Filter-Aided Sample Preparation (FASP) method was set up and performed. This bio-analytical strategy combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics, greatly reduces the time required for sample preparation and enables more flexibility in sample processing. Protein identification and quantification were performed by matching mass spectrometry data in on-line protein database, using the MaxQuant 1.5.2.8 software. Statistical analyses were employed to identify proteins whose levels were sensibly different in the umbilical cords from malformed fetuses. Gene Ontology (GO) classification was used in order to obtain functional information of the differentially expressed proteins and to correlate them to the embryonic development. Finally, Matrix Metalloproteinases (MMPs) have been shown to play significant roles in a number of physiological processes, including embryogenesis and angiogenesis, but they also contribute to the development of pathological processes. Thus, gelatin zymography technique was performed to detect MMPs enzymatic activity in the umbilical cords. Our results support a significant role of MMPs in the fetus development. [edited by author]
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Harris, Justin Clay. "NEW BIOINFORMATIC TECHNIQUES FOR THE ANALYSIS OF LARGE DATASETS." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_diss/544.

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A new era of chemical analysis is upon us. In the past, a small number of samples were selected from a population for use as a statistical representation of the entire population. More recently, advancements in data collection rate, computer memory, and processing speed have allowed entire populations to be sampled and analyzed. The result is massive amounts of data that convey relatively little information, even though they may contain a lot of information. These large quantities of data have already begun to cause bottlenecks in areas such as genetics, drug development, and chemical imaging. The problem is straightforward: condense a large quantity of data into only the useful portions without ignoring or discarding anything important. Performing the condensation in the hardware of the instrument, before the data ever reach a computer is even better. The research proposed tests the hypothesis that clusters of data may be rapidly identified by linear fitting of quantile-quantile plots produced from each principal component of principal component analysis. Integrated Sensing and Processing (ISP) is tested as a means of generating clusters of principal component scores from samples in a hyperspectral near-field scanning optical microscope. Distances from the centers of these multidimensional cluster centers to all other points in hyperspace can be calculated. The result is a novel digital staining technique for identifying anomalies in hyperspectral microscopic and nanoscopic imaging of human atherosclerotic tissue. This general method can be applied to other analytical problems as well.
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Rohen, V. E. "Applications of statistical pattern recognition techniques to the analysis of ballistocardiograms." Thesis, University of Cambridge, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235284.

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This dissertation describes a new approach to the analysis of Ballisto-cardiograms using Statistical Pattern Recognition technique, as well as the design and development of a new ballistocardiograph and its associated software. Ballistocardiograms are the result of forces exerted on the body, caused by the ejection of blood from the heart and the passage of the blood through the arterial system. The apparatus used in this study for the collection and display of the ballistocardiograms consisted of a specially designed stool with highly sensitive piezoelectric elements, which converted the forces acting on the stool into electric signals, connected to a specially built interface which converted the analogue signal into digital data. These were in turn analysed using a BBC model B microcomputer running special software which was written as part of this work. The methods of analysis developed here are based on Statistical Pattern Recognition and consist of units dealing with the preprocessing of the data, extraction of optimal features, and with their classification. By their nature, the lengths of the ballistocardiograms vary not only from person to person but there are also differences between the lengths of individual beats in the same subject. This presents a major problem for successful analysis. A novel method for non-linear standardisation of the ballistocardiogram length was developed and used in this study. This method allows the comparison of ballistocardiograms of different lengths, by projecting them into a waveform of uniform length, whilst maintaining all the information contained in the shape of the original signal. The projection is based on local cross-correlation of a template ballistocardiogram with a subset of the ballistocardiograms to be analysed. This results in a set of standard length records which in turn are used to determine the transformation. A feature extraction method based on double eigenanalysis was used to reduce the dimensionality of the data and for the extraction of features which discriminate best between the different classes analysed. Four classes of subjects were used in this study. A normal group which consisted of generally healthy and physically fit people, whose ballistocardiograms were also used to develop the new method for length adjustments; a group of subjects with mild hypertension; a group of patients with coronary artery stenosis, who were undergoing treatment at the Papworth Hospital; and a group consisting of subjects with clinical history of recent myocardial infarction. It was found that after standardisation of the length of the ballistocardiograms, and after extraction of those features which contain most of the discriminant information, the Nearest- Neighbour rule discriminated well between the group of normal subjects and the three remaining groups. The groups of subjects with mild hypertension and with coronary artery stenosis proved more difficult to separate. This can possibly be explained by the similarities in the characteristics of these two groups as far as ballistocardiograms are concerned. It was also found that the parts of the wave that have most of the discriminatory information are those corresponding to the ejection phase, for all the groups in general, and those corresponding to the last peaks of the ballistocardiograms (post ejection phase), for the group with recent myocardial infarction. Ballistocardiography is shown in this work to be a good non- invasive method for the study of the general performance of the heart. The methods described here for discrimination between groups and classification of different ballistocardiograms, by means of the analysis of their shape alone, have also proved very powerful. In particular, the new length standardisation method allows a more accurate monitoring of the heart function, than could be achieved so far. The techniques developed in this researh may be used for the prediction of various heart diseases in their early stages. This, together with the portability of the apparatus developed in this research, could turn the new ballistocardiograph into a standard clinical device.
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Jeon, Seonghye. "Bayesian data mining techniques in public health and biomedical applications." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43712.

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The emerging research issues in evidence-based healthcare decision-making and explosion of comparative effectiveness research (CER) are evident proof of the effort to thoroughly incorporate the rich data currently available within the system. The flexibility of Bayesian data mining techniques lends its strength to handle the challenging issues in the biomedical and health care domains. My research focuses primarily on Bayesian data mining techniques for non-traditional data in this domain, which includes, 1. Missing data: Matched-pair studies with fixed marginal totals with application to meta-analysis of dental sealants effectiveness. 2. Data with unusual distribution: Modeling spatial repeated measures with excess zeros and no covariates to estimate U.S. county level natural fluoride concentration. 3. Highly irregular data: Assess overall image regularity in complex wavelet domain to classify mammography image. The goal of my research is to strengthen the link from data to decisions. By using Bayesian data mining techniques including signal and image processing (wavelet analysis), hierarchical Bayesian modeling, clinical trials meta-analyses and spatial statistics, this thesis resolves challenging issues of how to incorporate data to improve the systems of health care and bio fields and ultimately benefit public health.
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Jakeway, Stephen Christopher. "Development of optical techniques for biomolecule detection in miniaturized total analysis systems." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271699.

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Seydnejad, Saeid Reza. "Analysis of heart rate variability and blood pressure variation by nonlinear modelling techniques." Thesis, Imperial College London, 1998. http://hdl.handle.net/10044/1/7814.

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D'Angelo, Maurissa S. "Analysis of Amputee Gait using Virtual Reality Rehabilitation Techniques." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1279121086.

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BERNACCHIA, NATASCIA. "Measurement techniques based on image processing for the assessment of biomedical parameters." Doctoral thesis, Università Politecnica delle Marche, 2014. http://hdl.handle.net/11566/242751.

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L’imaging biomedicale rappresenta un tema importante nel settore della diagno-si e della ricerca clinica. I software per l’analisi delle immagini permettono di individuare automaticamente informazioni non visibili all’occhio umano. Lo sviluppo tecnologico e l'u-so di diverse modalità di imaging aprono una sfida circa la necessità di analizzare un volu-me significativo di immagini per garantire informazioni di alta qualità per diagnosi, tratta-mento e monitoraggio, in strutture cliniche così come a casa. I sistemi di misura comunemente impiegati in ambiente clinico richiedono il contatto con il soggetto, provocando discomfort e risultando non adatti per tempi di osservazione lunghi. D'altra parte, il contatto può alterare la forma, la composizione dei campioni, e tecniche al-lo stato dell'arte potrebbero richiedere molto tempo e fornire bassa risoluzione. Questa tesi di dottorato presenta una serie di applicazioni sperimentali originali dell’analisi di immagini in campo biomedicale. L'obiettivo è quello di sviluppare e validare nuove me-todologie, basate sull’analisi di immagini, per la misura senza contatto di grandezze di di-versa natura. Lo studio tratta come prima applicazione l'estrazione di caratteristiche morfologiche di ag-gregati cellulari per studiare i processi di rigenerazione in cuori infartuati, poi lo sviluppo di una metodologia senza contatto per la misura delle proprietà meccaniche dei tendini rotulei di coniglio sottoposti a prove di trazione, e di metodi innovativi per il monitoraggio dei pa-rametri fisiologici (frequenza cardiaca e respiratoria, variazioni di volume del torace) usan-do sistemi quali il dispositivo Kinect ™ e una camera digitale. I banchi sperimentali, progettati in questo lavoro, sono stati validati, ottenendo un'elevata correlazione rispetto ai metodi di riferimento. I sistemi, seppur diversi per molti aspetti, hanno dimostrato di essere adatti ai rispettivi compiti, confermando la fattibilità dell’approccio basato sull’imaging biomedicale.
Biomedical imaging represents an important topic in the field of diagnosis and clinical research. Image analysis and processing software also helps to automatically identify what might not be apparent to the human eye. The technological development and the use of different imaging modalities create more challenges, as the need to analyse a significant volume of images so that high quality information can be produced for disease diagnosis, treatment and monitoring, in clinical structures as well as at home. All the measurement systems routinely used in clinical environment require to be put in di-rect contact with the subject, which in some cases can be uncomfortable or even non-suited for long monitoring. On the other hand, in some cases contact could alter shape or composition of the samples under study, and state-of-the-art techniques could require a lot of time and provide very low resolution. This doctoral thesis presents a series of new experimental applications of the image analysis and processing in the biomedical field. The aim was to develop and validate new method-ologies, based on image analysis, for non contact measurement of quantities of different nature. The study is focused on the extraction of morphological characteristics of cell ag-gregates to assess of the regeneration processes in infarcted hearts, the design of a non con-tact methodology to measure mechanical properties of rabbit patellar tendons subjected to tensile tests, the development of new methods for the monitoring of physiological parame-ters (heart and respiration rate, chest volume variations) through the use of image acquisi-tion systems, as Kinect™ device and a digital camera. The experimental setups, designed in this work, were validated, showing high correlation respect to the reference methods. Imaging systems, although so different in many aspects, have demonstrated to be suitable for the respective tasks, confirming the feasibility of the imaging approach in the biomedical field.
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Graça, Cristo dos Santos Lopes Ruano Maria da. "Investigation of real-time spectral analysis techniques for use with pulsed ultrasonic Doppler blood flow detectors." Thesis, Bangor University, 1992. https://research.bangor.ac.uk/portal/en/theses/investigation-of-realtime-spectral-analysis-techniques-for-use-with-pulsed-ultrasonic-doppler-blood-flow-detectors(f184d2a8-bde7-492a-b487-438704d3ea04).html.

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The goals of the work described here were the development of a method of selection of spectral estimation for use with pulsed Doppler ultrasonic blood flow instruments, and the use of this method to select an estimator and its implementation in a form suitable for real-time applications. A study of estimation accuracy of the mean frequency and bandwidth using a number of spectral estimators was carried out. Fourier based, parametric, and, minimum variance estimators were considered. A Doppler signal simulator was developed to allow the accuracy tests required. A method of selection of spectral estimators based on the accuracy of estimation of decisive signal parameters, under the constraint of low computational complexity has been proposed. This novel cost/benefit criterion, allows the possibility of weighting appropriate to estimator (mean frequency and bandwidth) and signal frequency importance (across the range of signal characteristics). For parametric spectral estimators, this criterion may also be used to select model order, leading to lower orders than FPE, AIC and CAT criteria. Its use led to the selection of a 4t' order modified covariance parametric method. A new version of the modified covariance method for spectral estimation of real signals was developed. This was created with a view to the parallel partitioning of the algorithm for parallel implementation on a transputer-based system, using OCCAM. A number of parallel topologies were implemented. Their performance was evaluated considering estimation of a single, and a sequence of Doppler signal segments, revealing the feasibility of these parallel implementations to be achieved in real-time.
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Kirk, E. M. "Biomedical applications of narrow-bore liquid chromatography with computer-aided detection : Application of multivariate digital techniques to biomedical samples in narrow-bore column high-performance liquid chromatography with photodiode array detection." Thesis, University of Bradford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384276.

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Books on the topic "Biomedical analysis techniques"

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Haidekker, Mark A. Advanced biomedical image analysis. Hoboken, N.J: John Wiley & Sons, 2010.

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1970-, Gonzalez Fabio A., and Romero Eduardo 1963-, eds. Biomedical image analysis and machine learning technologies: Applications and techniques. Hershey, PA: Medical Information Science Reference, 2010.

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Karaa, Wahiba Ben Abdessalem, and Nilanjan Dey. Biomedical image analysis and mining techniques for improved health outcomes. Hershey PA: Medical Information Science Reference, 2016.

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1970-, Gonzalez Fabio A., and Romero Eduardo 1963-, eds. Biomedical image analysis and machine learning technologies: Applications and techniques. Hershey, PA: Medical Information Science Reference, 2010.

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Norio, Ichinose, ed. Fluorometric analysis in biomedical chemistry: Trends and techniques including HPLC applications. New York: Wiley, 1991.

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Srinivasan, Gokulakrishnan. Vibrational spectroscopic imaging for biomedical applications. New York: McGraw-Hill, 2010.

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M, Cullum Brian, Carter J. Chance, and Society of Photo-optical Instrumentation Engineers., eds. Smart medical and biomedical sensor technology IV: 3-4 October 2006, Boston, Massachusetts, USA. Bellingham, Wash., USA: SPIE, 2006.

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Cullum, Brian M., and Eric S. McLamore. Smart biomedical and physiological sensor technology IX: 26 April 2012, Baltimore, Maryland, United States. Edited by SPIE (Society). Bellingham, Wash: SPIE, 2012.

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Gannot, Israel. Optical fibers, sensors, and devices for biomedical diagnostics and treatment XI: 22-23 January 2011 San Francisco, California, United States. Bellingham: sponsored and published by SPIE, 2011.

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Cullum, Brian M. Smart biomedical and physiological sensor technology VI: 16-17 April 2009, Orlando, Florida, United States. Bellingham, Wash: SPIE, 2009.

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Book chapters on the topic "Biomedical analysis techniques"

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Nisar, Muhammad Shemyal, and Xiangwei Zhao. "Nanophotonic Techniques for Single-Cell Analysis." In Nanophotonics in Biomedical Engineering, 79–109. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6137-5_4.

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Feng, Ting, Weiya Xie, Wenyi Xu, Ya Gao, Teng Liu, Dean Ta, Menglu Qian, and Qian Cheng. "Photoacoustic Techniques for Bone Characterization." In Biomedical Photoacoustics, 433–75. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61411-8_17.

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AbstractBiomedical photoacoustics (PA) combines the advantages of selective optical absorption of biological tissues and high penetration depth of ultrasound, providing information on the macroscopic physiological structure and microscopic molecular level of biological tissues. Thus, it has great potential in the application of biomedical diagnosis. Among them, PA detection of bone is an important branch. In contrast to soft tissue, which can be regarded as a homogeneous medium, bone tissue is a two-phase complex medium (mineralized bone trabecular network in the solid phase and embedded bone marrow in the liquid phase), and this anisotropic and heterogeneous structure poses significant challenges to bone tissue characterization methods based on PA technology. This chapter introduces our work on PA detection for complex bone tissue, including the principle of PA wave generation and propagation, the methods of PA imaging and spectrum analysis, and their clinical applications. Finally, this chapter analyzes the current challenges in this field and anticipates future development trends based on the current research status of the PA technology.
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Henao Higuita, María Camila, Macheily Hernández Fernández, Delio Aristizabal Martínez, and Hermes Fandiño Toro. "Analysis of Finger Thermoregulation by Using Signal Processing Techniques." In Bioinformatics and Biomedical Engineering, 537–49. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17935-9_48.

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Dussaut, J. S., C. A. Gallo, J. A. Carballido, and I. Ponzoni. "Analysis of Gene Expression Discretization Techniques in Microarray Biclustering." In Bioinformatics and Biomedical Engineering, 257–66. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56154-7_24.

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Puentes Vargas, Margarita. "Extraction Techniques." In Planar Metamaterial Based Microwave Sensor Arrays for Biomedical Analysis and Treatment, 33–45. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06041-5_3.

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Pradhan, Jitesh, Arup Kumar Pal, and Haider Banka. "Medical Image Retrieval System Using Deep Learning Techniques." In Deep Learning for Biomedical Data Analysis, 101–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71676-9_5.

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Scriba, Gerhard K. E. "Chiral electromigration techniques in pharmaceutical and biomedical analysis." In Frontiers of Bioanalytical Chemistry, 225–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-36303-0_11.

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Tina and Ritu Gupta. "Analysis of deep learning techniques in biomedical images." In Artificial Intelligence and Blockchain in Industry 4.0, 78–94. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003452591-6.

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Prabha, R., V. Subashini, M. Aishwarya, B. Hemalatha, and A. Sadhana. "Analysis of antenna for biomedical applications." In Antennas for Industrial and Medical Applications with Optimization Techniques for Wireless Communication, 151–61. Boca Raton: CRC Press, 2024. https://doi.org/10.1201/9781003560487-10.

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Kaur, Raj Kamal, and Sarneet Kaur. "Exploring explainable AI: Techniques and comparative analysis." In Explainable Artificial Intelligence for Biomedical and Healthcare Applications, 1–14. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003220107-1.

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Conference papers on the topic "Biomedical analysis techniques"

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Salazar, Sara Valentina Hernández, Javier Chaparro Preciado, and Santiago Agudo Muñoz. "Comparative Analysis of Machine Learning and Deep Learning Techniques for Hand Gesture Recognition Using Surface Electromyography." In 2024 3rd International Congress of Biomedical Engineering and Bioengineering (CIIBBI), 1–6. IEEE, 2024. https://doi.org/10.1109/ciibbi63846.2024.10784625.

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Migla, Sandis, Oskars Selis, Pauls Eriks Sics, and Arturs Aboltins. "Error Analysis and Correction Techniques for PPM Communication Links with Jitter and Clock Drift." In 2024 IEEE International Conference on Microwaves, Communications, Antennas, Biomedical Engineering and Electronic Systems (COMCAS), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/comcas58210.2024.10666259.

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Cerri, G., R. De Leo, and A. Spalvieri. "Microstrip Disk Applicators for Biomedical Applications: A Very Efficient Numerical Analysis Technique." In EMC_1986_Wroclaw, 62–70. IEEE, 1986. https://doi.org/10.23919/emc.1986.10828529.

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Ma, Jianguo, Min Wei, Lijun Xu, Boya Chen, Yulin Liu, Jie Du, and Zijie Fang. "Ultrasonic spectral analysis for biomedical imaging." In 2017 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2017. http://dx.doi.org/10.1109/ist.2017.8261549.

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Essa, Hayder J., and Issa Jaafar. "New analysis techniques for blood pressure biomedical signals." In 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA). IEEE, 2014. http://dx.doi.org/10.1109/wartia.2014.6976177.

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Chen, Xuequan, Emma Pickwell-MacPherson, Qiushuo Sun, Jiarui Wang, Hannah Lindley, Kai Liu, Kaidi Li, Xavier Barker, Rayko Stantchev, and Arturo Hernandez. "THz Instrumentation and Analysis Techniques for Biomedical Research." In 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz). IEEE, 2019. http://dx.doi.org/10.1109/irmmw-thz.2019.8874398.

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Robb, Richard A., Armando Manduca, Dennis P. Hanson, and Ronald A. Karwoski. "Advanced techniques in volume visualization and analysis." In Visualization in Biomedical Computing, edited by Richard A. Robb. SPIE, 1992. http://dx.doi.org/10.1117/12.131124.

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Ortiz, Sergio, Pablo Pérez-Merino, Enrique Gambra, and Susana Marcos. "Image analysis and quantification in anterior segment OCT: techniques and applications." In Biomedical Optics. Washington, D.C.: OSA, 2012. http://dx.doi.org/10.1364/biomed.2012.btu2b.6.

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Costea, I. M., C. I. Dumitrescu, N. Dumitru, and B. Soare. "Biomedical signals analysis techniques using the signal processor TMS320C6211B." In 2014 37th ISSE International Spring Seminar in Electronics Technology (ISSE). IEEE, 2014. http://dx.doi.org/10.1109/isse.2014.6887617.

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Gaeta, Giovanni M., Flora Zenone, Carlo Camerlingo, Roberto Riccio, Gianfranco Moro, Maria Lepore, and Pietro L. Indovina. "Data analysis in Raman measurements of biological tissues using wavelet techniques." In Biomedical Optics 2005, edited by Peter Rechmann and Daniel Fried. SPIE, 2005. http://dx.doi.org/10.1117/12.593394.

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Reports on the topic "Biomedical analysis techniques"

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Vingre, Anete, Peter Kolarz, and Billy Bryan. On your marks, get set, fund! Rapid responses to the Covid-19 pandemic. Fteval - Austrian Platform for Research and Technology Policy Evaluation, April 2022. http://dx.doi.org/10.22163/fteval.2022.538.

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Abstract:
This paper presents findings from an analysis of seven multidisciplinary national research funders’ responses to COVID-19. We posit that while some parts of research and innovation funding responses to COVID-19 were ‘pandemic responses’ in the conventional biomedical sense, other parts were thematically far broader and are better termed ‘societal emergency’ funding. This type of funding activity was unprecedented for many funders. Yet, it may signal a new/additional mission for research funders, which may be required to tackle future societal emergencies, medical or otherwise. Urgency (i.e., the need to deploy funding quickly) is a key distinguishing theme in these funding activities. This paper explores the different techniques that funders used to substantially speed up their application and assessment processes to ensure research on COVID-19 could commence as quickly as possible. Funders used a range of approaches, both before application submission (call design, application lengths and formats) and after (review and decision-making processes). Our research highlights a series of trade-offs, at the heart of which are concerns around simultaneously ensuring the required speed as well as the quality of funding-decisions. We extract some recommendations for what a generic ‘societal emergency’ funding toolkit might include to optimally manage these tensions in case national research funders are called upon again to respond to future crises.
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