PathBind / README.md
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Initial upload: PathBind-VQA + PathBind-PTA + PathBind-Grounding
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---
license: cc-by-nc-4.0
task_categories:
- visual-question-answering
- object-detection
language:
- en
- zh
tags:
- pathology
- medical-imaging
- benchmark
- vqa
- grounding
size_categories:
- 1K<n<10K
pretty_name: PathBind
configs:
- config_name: PathBind-VQA
data_files:
- split: manifest
path: PathBind-VQA/manifest.tsv
- config_name: PathBind-PTA
data_files:
- split: eval
path: PathBind-PTA/pathbind_pta_600.tsv
- config_name: PathBind-Grounding
data_files:
- split: manifest
path: PathBind-Grounding/manifest.jsonl
extra_gated_prompt: >-
PathBind is released for non-commercial research use only. It is NOT
certified for clinical diagnostic use. By requesting access you agree to
(1) non-commercial use, (2) no redistribution of the manifest, images, or
derivatives, (3) citing the PathBind paper in any publication that uses
the dataset, (4) obtaining the underlying source datasets (PathMMU,
Path-VQA, Quilt-VQA, MedXpert-Path, OmniMed-Bright, PathVG) under their
own licenses when using the VQA / Grounding manifests, and (5) not using
PathBind-PTA to inform patient care. Fill in the fields below; we aim to
review within five business days.
extra_gated_fields:
Full name: text
Affiliation: text
Email (institutional preferred): text
Country: country
Intended use: text
I agree to use PathBind for non-commercial research only: checkbox
I agree not to redistribute the manifest, images, or derivatives: checkbox
I understand PathBind-PTA is not for clinical use: checkbox
extra_gated_button_content: Request access
---
# PathBind
**A diagnostic benchmark for evaluating pathology vision-language models.**
PathBind bundles 2,600 samples across three components — each filtered by
an automated pipeline and finalized under expert pathologist review — to
jointly probe visual dependence, cross-domain replication, and
entity-level visual-semantic binding.
| Config | # samples | Format |
|------------------------|----------:|-----------------------------------------|
| `PathBind-VQA` | 1,500 | sample-ID manifest (TSV) |
| `PathBind-PTA` | 600 | self-contained TSV, base64 JPEGs inline |
| `PathBind-Grounding` | 500 | sample-ID manifest (JSONL) |
## Diagnostic dimensions
| Dim. | Name | Definition |
|:----:|---------------------------------|------------------------------------------------------------------|
| D1 | Coarse tissue/organ recognition | Broad tissue type, organ context, general histologic category. |
| D2 | Cellular morphology | Nuclear atypia, cytoplasm, mitotic figures, necrosis. |
| D3 | Cell–stroma interaction | Infiltration pattern, inflammatory distribution, desmoplasia. |
| D4 | Spatial localization | Spatial position, arrangement, or distribution of structures. |
| D5 | Diagnostic reasoning | Integrated visual evidence for diagnosis, grading, staging. |
| D6 | Staining & IHC interpretation | Staining patterns, IHC positivity, intensity/distribution. |
## Repository layout
```
PathBind/
├── PathBind-VQA/ # 1,500 sample IDs (D1–D6 × 250)
│ └── manifest.tsv
├── PathBind-PTA/ # 600 self-contained samples (D1–D5 × 120)
│ └── pathbind_pta_600.tsv
└── PathBind-Grounding/ # 500 sample IDs (testA 380 + testB 120)
└── manifest.jsonl
```
## Usage
### PathBind-VQA
We ship only sample IDs. Obtain the five source benchmarks yourself, then
materialize the full TSV with the PathBind evaluation repo:
```bash
git clone https://github.com/<org>/PathBind
python pathbind/data/PathBind-VQA/build.py \
--pathmmu_dir /path/to/PathMMU \
--pathvqa_dir /path/to/Path-VQA \
--quiltvqa_dir /path/to/Quilt-VQA \
--omnimed_dir /path/to/OmniMed-Bright \
--medxpert_dir /path/to/MedXpert-Path
```
Fields: `index`, `dimension`, `source_dataset`, `source_sample_id`, `answer_type`.
Composition: PathMMU 1,311 · OmniMed-Bright 102 · Path-VQA 37 · Quilt-VQA 25 · MedXpert-Path 25.
### PathBind-Grounding
Similarly, obtain PathVG and materialize:
```bash
python pathbind/data/PathBind-Grounding/build.py --pathvg_dir /path/to/PathVG
```
Fields: `split`, `image_id`, `bbox_id`, `expression`, `bbox`, `width`, `height`.
### PathBind-PTA
Self-contained — no external download needed. Follows the PathoSage TSV
convention: the `image` column contains **base64-encoded JPEG** data (long
side ≤ 1024 px, quality 85).
Balanced across five diagnostic dimensions (D1–D5, 120 each) and answer
options (A–D, 150 each).
## Running an evaluation
```bash
git clone https://github.com/<org>/PathBind
cd PathBind
python -m pathbind.eval_a1 \
--data PathBind-VQA/pathbind_vqa_1500.tsv \
--model_module pathbind.models.patho_r1 --ckpt /path/to/Patho-R1 \
--out results/vqa.jsonl
```
Replace `--data` with the PTA or Grounding materialized file for the
other two components. See the PathBind code repo README for the full API
and how to port a new model.
## Citation
Coming soon.
## License
- `PathBind-VQA` and `PathBind-Grounding` manifests: MIT. Referenced source
datasets remain under their **original licenses** — please follow the
terms of PathMMU / Path-VQA / Quilt-VQA / MedXpert-Path / OmniMed-Bright /
PathVG when using them.
- `PathBind-PTA` component: **CC BY-NC 4.0** (non-commercial research use
only, not for clinical use).