Pancreatic  Cancer  (PC)  is  a  very  aggressive  cancer,  with  a  mortality  of  0.98  and  a  5-year  survival  rate  of 6.7%. Endoscopic  ultrasonography  (EUS)  is  the  imaging  modality  to  early  detection  of  PC.  Its  reported diagnosis sensitivity for an experienced gastroenterologist ranges from 87 to 100%. Computational strategies, as Elastography, have been developed to support mass malignancy diagnosis.  However, most studies evaluate their strategies using private datasets, making results incomparable. This work presents an annotated open access database of Endoscopy Ultrasound videos obtained in the Gastroenterology Unit of the Hospital UniversitarioNacional  de  Colombia  and  the  Unidad  de  Gastroenterología  y  Ecoendoscopia.   The  dataset  consists  in  a  set of 55 cases acquired in B-mode Ultrasound image, composed of 18 cases with pancreatic cancer, 5 cases with pancreatitis, and 32 cases that include healthy pancreas, liver and gallbladder.  Cases were confirmed and staged by pathological examination from biopsy samples and manually annotated per each video frame.  Additionally, herein it is presented a preprocessing methodology aimed to highlight the useful echo patterns to differentiate pancreatic diseases.

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If you use our database please cite us:
https://doi.org/10.1117/12.2581321