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Developing the framework for an open-source platform for large-scale micro-computed tomography data
Open-source strategies are becoming increasingly popular among researchers. Measured micro-computed tomography (micro-CT) data sets can be used as training sets for machine learning algorithms or validation sets of in silico simulations. To date, such undertakings face the lack of access to such experimental data. This student project will develop a novel open-research data platform for large micro-CT datasets which facilitate the exchange among research communities.
Micro-computed tomography is a well-established method for non-destructive high-resolution visualization and analysis of the inner structure of bone. Researchers in the bone community would benefit from access to open-access imaging data as input for their research questions. In recent years, several open-research databases have been created, for example international projects such as the Human Genome Project or ENCODE. In bone research, large amounts of data are accumulated. However, no large database of these images is available to date. We want to create the first open research data repository for micro-computed tomography data. By collating the images in a repository that makes them easily accessible, we hope to inspire the scientific community to re-use existing data for their novel projects.
Among our images are, for example, more than 2000 mouse femurs, 700 mouse vertebrae, serial images from bone samples during image guided failure assessment which allows the observation of microcrack propagation and bone fracturing by stepwise compression, an image series of bone healing with or without implanted materials and with mechanical loading. Another large set of images consists of human bone biopsies which were imaged at medium and high resolution. A smaller number of human samples was obtained post mortem; among these are bone showing rare diseases for a historical collection. These images are a valuable training data resource for machine learning-based algorithms, however they need to be made visible to the research community. To provide a web-based application to allow search, order and visual inspection of the available datasets will be the topic of this student project.
Micro-computed tomography is a well-established method for non-destructive high-resolution visualization and analysis of the inner structure of bone. Researchers in the bone community would benefit from access to open-access imaging data as input for their research questions. In recent years, several open-research databases have been created, for example international projects such as the Human Genome Project or ENCODE. In bone research, large amounts of data are accumulated. However, no large database of these images is available to date. We want to create the first open research data repository for micro-computed tomography data. By collating the images in a repository that makes them easily accessible, we hope to inspire the scientific community to re-use existing data for their novel projects. Among our images are, for example, more than 2000 mouse femurs, 700 mouse vertebrae, serial images from bone samples during image guided failure assessment which allows the observation of microcrack propagation and bone fracturing by stepwise compression, an image series of bone healing with or without implanted materials and with mechanical loading. Another large set of images consists of human bone biopsies which were imaged at medium and high resolution. A smaller number of human samples was obtained post mortem; among these are bone showing rare diseases for a historical collection. These images are a valuable training data resource for machine learning-based algorithms, however they need to be made visible to the research community. To provide a web-based application to allow search, order and visual inspection of the available datasets will be the topic of this student project.
The goal of this student project is to:
- implement the framework for a web-based application for easy share of large micro-computed tomography datasets
- setup a prototype of the database framework including a graphical interface, and allow the upload of first datasets in different formats
- test, report and document features and results.
Prerequisites:
- programming skills in Java, PHP or other web-based programming language
- experience with MySQL or Oracle server architectures
- joy in learning new things
The goal of this student project is to:
- implement the framework for a web-based application for easy share of large micro-computed tomography datasets
- setup a prototype of the database framework including a graphical interface, and allow the upload of first datasets in different formats
- test, report and document features and results.
Prerequisites:
- programming skills in Java, PHP or other web-based programming language
- experience with MySQL or Oracle server architectures
- joy in learning new things
Friederike Schulte (friederike.schulte@hest.ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Gisela Kuhn (gakuhn@ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Amit Singh (amit.singh@hest.ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Friederike Schulte (friederike.schulte@hest.ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Gisela Kuhn (gakuhn@ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller
Amit Singh (amit.singh@hest.ethz.ch) Institute for Biomechanics, ETH Zurich, Professorship Ralph Müller