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Cet.CT-Bank: A Postmortem Computed Tomography Imaging Data of Stranded Cetaceans from the Canary Islands.

July 15, 2026pubmed logopapers

Authors

Suárez-Santana CM,Consoli FMA,Alonso-Almorox P,Reyes-Matute A,Arbelo M,Hernández-López R,Travieso-González CM,Rivero MA,Fernández A

Affiliations (3)

  • Unit of Veterinary Histology and Pathology, University Institute of Animal Health and Food Safety (IUSA), Veterinary School, University of Las Palmas de Gran Canaria (ULPGC), 35413, Las Palmas de Gran Canaria, Spain.
  • Signals and Communications Department (DSC), Institute for Technological Development and Innovation in Communications (IDeTIC), University of Las Palmas de Gran Canaria (ULPGC), 35017, Las Palmas de Gran Canaria, Spain.
  • Unit of Veterinary Histology and Pathology, University Institute of Animal Health and Food Safety (IUSA), Veterinary School, University of Las Palmas de Gran Canaria (ULPGC), 35413, Las Palmas de Gran Canaria, Spain. [email protected].

Abstract

Post-mortem computed tomography (PMCT) has become an increasingly important tool in cetacean stranding investigation, providing reusable, three-dimensional data of internal anatomical structures. Here, we present Cet.CT-Bank, a PMCT imaging dataset derived from stranded cetaceans recovered along the Canary Islands coast. The dataset comprises eight odontocete specimens representing six cetacean species, scanned using standardized CT protocols and stored as DICOM files with complete acquisition and reconstruction metadata. Each case is accompanied by automatically generated validation reports, ensuring traceability and reproducibility of the imaging data. Biological and pathological information is provided within this data descriptor and its supplementary materials to support integrative interpretation. Cet.CT-Bank is intended as an open, reusable imaging resource for morphological research, veterinary pathology, forensic investigation, and the development and validation of computational image analysis methods, including applications in computational image analysis, with potential relevance for future artificial intelligence-based approaches.

Topics

Journal Article

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