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.
Auletta et al. (Thu,) studied this question.