Curie-Cancer and Strand develop breakthrough platform

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Curie-Cancer, the body responsible for developing Institut Curie's industry partnership activity, and Strand Scientific Intelligence have launched the Curie Image Database (CID). The database is a breakthrough image analysis and management platform that was developed over the last two years at the Cell and Tissue Imaging Core Facility of the Institut Curie in France.

CID was created using Strand’s award-winning Avadis platform. It now enables over 250 scientists at the Institute and ten other collaborating institutions across Europe to effectively manage heterogeneous imaging data and complex analysis workflows. CID provides shared, secure and open access to image life cycle data as well as image analysis algorithms.

Professor Vijay Chandru, co-founder and CEO of Strand said: ‘Institut Curie’s expertise in advanced imaging platforms and Strand's ability to engineer superior scientific software have come together to create a scalable, secure and efficient “open access” platform for microscopy images and analysis algorithms. Going forward we would like to explore, with Institut Curie, an advanced decision support platform for oncologists that integrates genomic signatures of cancers and imaging data towards better diagnosis and treatment of cancer patients.’

Jean Salamero, scientific director of Cell and Tissue Imaging Core Facility at Curie-Cancer stated: ‘Our goal was not only to provide an image management system, but also an interactive research tool that allows data and analysis sharing for distant and multidisciplinary projects between teams from different labs and institutes, that is able to handle the exponential growth and complexity of scientific and biomedical images generated by advanced microscopy systems.’

Salamero explained: ‘Funding through the France Bio-Imaging program and Canceropole-IdF, a French network of institutions dedicated to oncology, allowed us to link CID to a new and secure storage infrastructure and to promote access to image processing on dedicated clusters. Going forward, we would like to integrate this image database with other types of data, like genomic data or clinical and anatomy-pathological data related to clinical projects, resulting in an even more effective weapon in our fight against cancer.'

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