qhjqhj00 corebt-eval
CoRe-BT: A Multimodal Radiology-Pathology-Text Benchmark for Robust Brain Tumor Typing — Heras Rivera et al. (2026) (arXiv:2603.03618, 2026)
What this evaluates
Evaluates multimodal fusion models for robust brain tumor typing by integrating MRI, histopathology, and diagnostic text under variable modality availability conditions. The benchmark probes a model's ability to perform fine-grained hierarchical classification across six glioma subtypes when some modalities are missing or degraded.
Datasets
- CoRe-BT — total 310; splits: train (-1), val (-1), test (-1)
Metrics
accuracy(primary) — range: [0, 1]- Standard classification accuracy measuring the proportion of correctly predicted glioma subtypes out of total patients. Exact metric variant (e.g., macro-F1) is not specified in the provided text.
Input / output format
Input: Per patient: 3D MRI volumes, whole-slide histopathology images (processed into 256x256 tiles), and diagnostic text.
Output: Hierarchical tumor classification label across six glioma subtypes.
Scoring recipe
def compute_accuracy(predictions, gold_labels):
correct = sum(1 for p, g in zip(predictions, gold_labels) if p == g)
return correct / len(gold_labels)
Common pitfalls
- Missing-modality robustness is a core evaluation condition, but specific missingness protocols, randomization seeds, or split configurations are not detailed in the provided text.
- Hierarchical labeling implies multi-level classification, but the exact evaluation hierarchy and how subtypes are mapped to labels are not specified.
Evidence (verbatim from paper)
The dataset includes 310 patients with expert-annotated tumor masks and pathologist-validated hierarchical labels across six glioma subtypes, enabling evaluation of multimodal fusion under missing-modality conditions. Baseline experiments demonstrate that multimodal models outperform MRI-only baselines, especially in distinguishing rare glioma subtypes.
Citation
@misc{herasrivera2026corebt,
title={CoRe-BT: A Multimodal Radiology-Pathology-Text Benchmark for Robust Brain Tumor Typing},
author={Heras Rivera et al. (2026)},
year={2026},
note={arXiv:2603.03618}
}
- arXiv: 2603.03618