Medical Imaging Processing on a Big Data Platform Using Python: Experiences with Heterogeneous and Homogeneous Architectures

Serrano, Estefania; Blas, Javier García; Carretero, Jesús; Abella, Mónica; Desco, Manuel

doi:10.1109/ccgrid.2017.56

Cited by 10 publications

(7 citation statements)

References 21 publications

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“…and the AW Thickness. The analysis was performed by the Python program language version 3.7.4 [22], using libraries like Scipy, Sklearn, Skimage, Matplotlib.Pyplot and Seaborn from the scientific package Anaconda distribution version 2019.10 (https://docs.anaconda.com/anaconda-cloud/faq/#what-isanaconda-inc).…”

Section: Abdominal Wall Thickness Assessment To Verify Ultrasound Attmentioning

confidence: 99%

Ultrasonography validation for early alteration of diaphragm echodensity and function in the mdx mouse model of Duchenne muscular dystrophy

et al. 2021

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The mdx mouse model of Duchenne muscular dystrophy is characterized by functional and structural alterations of the diaphragm since early stages of pathology, closely resembling patients’ condition. In recent years, ultrasonography has been proposed as a useful longitudinal non-invasive technique to assess mdx diaphragm dysfunction and evaluate drug efficacy over time. To date, only a few preclinical studies have been conducted. Therefore, an independent validation of this method by different laboratories is needed to increase results reliability and reduce biases. Here, we performed diaphragm ultrasonography in 3- and 6-month-old mdx mice, the preferred age-window for pharmacology studies. The alteration of diaphragm function over time was measured as diaphragm ultrasound movement amplitude. At the same time points, a first-time assessment of diaphragm echodensity was performed, as an experimental index of progressive loss of contractile tissue. A parallel evaluation of other in vivo and ex vivo dystrophy-relevant readouts was carried out. Both 3- and 6-month-old mdx mice showed a significant decrease in diaphragm amplitude compared to wild type (wt) mice. This index was well-correlated either with in vivo running performance or ex vivo isometric tetanic force of isolated diaphragm. In addition, diaphragms from 6-month-old dystrophic mice were also highly susceptible to eccentric contraction ex vivo. Importantly, we disclosed an age-dependent increase in echodensity in mdx mice not observed in wt animals, which was independent from abdominal wall thickness. This was accompanied by a notable increase of pro-fibrotic TGF-β1 levels in the mdx diaphragm and of non-muscle tissue amount in diaphragm sections stained by hematoxylin & eosin. Our findings corroborate the usefulness of diaphragm ultrasonography in preclinical drug studies as a powerful tool to monitor mdx pathology progression since early stages.

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Section: Abdominal Wall Thickness Assessment To Verify Ultrasound Attmentioning

confidence: 99%

Ultrasonography validation for early alteration of diaphragm echodensity and function in the mdx mouse model of Duchenne muscular dystrophy

et al. 2021

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“…With much growth in clinical and biomedical data, visual analytics seems to have a vibrant future on this premise. A promising big data programming framework used to deal with health care data is the MapReduce framework (software framework for processing large volumes of data) that processes huge volumes of imaging data (Panayides et al , 2017; Serrano et al , 2017). Another example of an emerging algorithm in video data processing is the CURE clustering algorithm which can be used to generate information related to various diseases.…”

Section: Trending/emerging Technologies Of Data Miningmentioning

confidence: 99%

Exploring data mining: facets and emerging trends

Gul

Bano

Shah

2021

DLP

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Purpose Data mining along with its varied technologies like numerical mining, textual mining, multimedia mining, web mining, sentiment analysis and big data mining proves itself as an emerging field and manifests itself in the form of different techniques such as information mining; big data mining; big data mining and Internet of Things (IoT); and educational data mining. This paper aims to discuss how these technologies and techniques are used to derive information and, eventually, knowledge from data. Design/methodology/approach An extensive review of literature on data mining and its allied techniques was carried to ascertain the emerging procedures and techniques in the domain of data mining. Clarivate Analytic’s Web of Science and Sciverse Scopus were explored to discover the extent of literature published on Data Mining and its varied facets. Literature was searched against various keywords such as data mining; information mining; big data; big data and IoT; and educational data mining. Further, the works citing the literature on data mining were also explored to visualize a broad gamut of emerging techniques about this growing field. Findings The study validates that knowledge discovery in databases has rendered data mining as an emerging field; the data present in these databases paves the way for data mining techniques and analytics. This paper provides a unique view about the usage of data, and logical patterns derived from it, how new procedures, algorithms and mining techniques are being continuously upgraded for their multipurpose use for the betterment of human life and experiences. Practical implications The paper highlights different aspects of data mining, its different technological approaches, and how these emerging data technologies are used to derive logical insights from data and make data more meaningful. Originality/value The paper tries to highlight the current trends and facets of data mining.

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“…The workshop had around 40 participants who attended to the final program composed of two sessions Session 1: •Serrano et al: Medical Imaging Processing on a Big Data Platform Using Python: Experiences With Heterogeneous and Homogeneous Architectures •Bogdanov et al: Analog‐Digital Approach in Human Brain Modeling •Hof et al: BIOPET: Towards Scalable, Maintainable, User‐Friendly, Robust and Flexible NGS Data Analysis Pipelines Session 2: •Gonzalez et al: Using the Cloud for Parameter Estimation Problems: Comparing Spark vs MPI With a Case‐Study •Witt et al: Fine‐Grained Supervision and Restriction of Biomedical Applications in Linux Containers •Panel Discussion: Perspectives and Challenges in Biomedical Analytics. Moderation: Dagmar Krefting. …”

Section: Workhop Program Highlightsmentioning

confidence: 99%