Sáiz, MónicaBelar, Oihanade Jong, BasKap, MarcelBereciartua, ArantzaRuiz, RebecaViguri, Maria AmparoRezola, Ricardode Miguel, EduardoSaiz, AlbertoFernández, SaraGaafar, AymanCatón, BlancaAguirre, JavierDoukas, MichaelMuñoz, ElenaGandon, FabienneRiegman, PeterBilbao, Roberto2016-06-072016-06-072015Conference: 26th European Congress of Pathology (ECP 2014), At London, United Kingdom, Volume: Virchows Archiv (2014) 465 (Suppl 1):S1–S3791432-2307http://hdl.handle.net/11556/241Objective: Searching tissues for research across biobanks and pathology departments is complicated due to the geographically dispersed distribution, diagnosis heterogeneity, language diversity and lack of online robust samples catalogues. BIOPOOL consortium (www.biopoolproject.eu) was created to give a solution based on a new search approach similar to Google images but focused on histological images and associated clinical databases. The project is funded by the 7FP of the European Commission (GA296162). Method: Digital images from colon, breast and lung cancer were used to develop the software. Eleven pathologists worked closely with IT developers. They defined the technical and functional requirements of the final system, and the identification and validation of the key visual features and regions of interest on the histological images and their associated data. Relevant visual descriptors were identified, coded and extracted automatically from the images in order to be included in the searching tool and retrieved later in the case it matches the query. Results: A new web-based search portal was developed to find tumor samples across biobanks based on query by image and/or text. The legal and ethical issues were taken in consideration. Conclusion: BIOPOOL network, is now open to biobanks and pathology departments to bring together, in a European scale, a research infrastructure that could help to conduct research through the synergy of medical knowledge and technology.engconference outputembargoed accesshistology imagecontent based image retrievalimage processingcomputer vision