[IMAGE] A multiscale imaging and modelling dataset of the human inner ear
We have relevant datasets, repositories, frameworks and tools of relevance for research and technology transfer initiatives related to knowledge extraction. This section provides an overview on a selection of them and links to download or contact details.
The MdM Strategic Research Program has its own community in Zenodo for material available in this repository
as well as at the UPF e-repository 
. Below a non-exhaustive list of datasets representative of the research in the Department.
As part of the promotion of the availability of resources, the creation of specific communities in Zenodo has also been promoted, at level of research communities (for instance, MIR and Educational Data Analytics) or MSc programs (for instance, the Master in Sound and Music Computing)
A multiscale imaging and modelling dataset of the human inner ear
Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in studies conducted with few samples. To assist the cochlear research community, a large collection of human temporal bone images is being made available. This data descriptor, therefore, describes a rich set of image volumes acquired using cone beam computed tomography and micro-CT modalities, accompanied by manual delineations of the cochlea and sub-compartments, a statistical shape model encoding its anatomical variability, and data for electrode insertion and electrical simulations. This data makes an important asset for future studies in need of high-resolution data and related statistical data objects of the cochlea used to leverage scientific hypotheses. It is of relevance to anatomists, audiologists, computer scientists in the different domains of image analysis, computer simulations, imaging formation, and for biomedical engineers designing new strategies for cochlear implantations, electrode design, and others.
See the related publication at Nature Scientific Data https://www.nature.com/articles/sdata2017132