Digital dataset enhances pathology evaluations in animal oncology, indicating improved accuracy and accessibility.
Macroscopic descriptions in anatomic pathology play a crucial role in the evaluation of tissue samples and, in diagnosis and treatment decisions of patients. This applies to biological specimens in both animal and human oncology. The presented DATP-IU dataset aims to serve as a pioneering effort, starting with animal samples, to create a digital atlas of histopathological tissue specimens at the macroscopic level, enriched with quantitative sensory data. The image and ultrasound data were obtained from formalin-fixed histological animal tissues of varying sizes, types, and origins. The data were analyzed using a rotary-stage coordinate system and compared with manual caliper measurements of the same calibration pattern. The average Z absolute error is 1.02%, and sub-millimeter accuracy is maintained across all camera distances. The automatic regulation of yaw angles via a LabVIEW routine enhanced both accuracy and repeatability by eliminating manual errors and ensuring consistent angular adjustments. The presented DATP-IU dataset offers an innovative approach to making pathology assessments more accurate, reproducible, and accessible.
No takes yet. Share an insight, caveat, or question.
Auletta et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: