Reproducibility metadata and experimental artifacts from a prostate cancer binary segmentation study using the public DIAGSET database
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Nunes, Bruno Henrique
DOI
Abstract
Description
This dataset contains reproducibility metadata, provenance records, configuration files, manifests, intermediate artifacts, and experimental results from a computational study on automated prostate cancer identification and binary segmentation in histopathological slide images. The study used the public DIAGSET database as the input image source; the original DIAGSET images are not redistributed in this deposit.
The deposited materials document how the research data were processed throughout the workflow, including artifact identification, patch and binary-mask extraction, quality control, graph-based cleaning, patient-level partitioning into training, validation, and test sets, color-normalization strategies, smart sampling of training patches, learning-rate selection, supervised segmentation model training, ensemble optimization, and final inference/evaluation.
The collection includes CSV manifests, SQLite provenance and execution databases, GeoJSON-related artifact metadata, patient-level split artifacts, sampling records, model-training metadata, ensemble configuration files, and quantitative evaluation outputs. Its purpose is to support verification, traceability, and reproducibility of the computational methodology used to study prostate cancer segmentation in histopathological images.