Datasets:

Kkkelsey
/

SPROUT

---
license: other
task_categories:
  - image-segmentation
tags:
  - pathology
  - nuclei-segmentation
  - medical-imaging
  - MoNuSeg
  - CPM17
  - TNBC
pretty_name: SPROUT Preprocessed Datasets
---
# SPROUT Preprocessed Datasets

This repository provides the **preprocessed datasets used in SPROUT**:

> **Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting**
> ICML 2026

Official code repository: https://github.com/Y-Research-SBU/SPROUT

## Datasets

The repository contains preprocessed versions of the following publicly available nuclear segmentation datasets:

* **MoNuSeg**
* **CPM17**
* **TNBC**

The datasets have been reorganized and preprocessed to match the data format expected by the SPROUT codebase.

## Directory Structure

The dataset follows the structure used by SPROUT:

```text
MoNuSeg/
├── train/
│   ├── annotations/
│   ├── images/
│   ├── instances/
│   ├── semantics/
│   ├── png/
│   └── train.txt
└── test/
    ├── annotations/
    ├── images/
    ├── instances/
    ├── semantics/
    ├── png/
    └── test.txt
cpm17/
...
TNBC/
...
```

## Usage

Download or clone the dataset and place the dataset folders under the `data/` directory of the SPROUT repository:

```text
SPROUT/
└── data/
    ├── MoNuSeg/
    ├── cpm17/
    └── TNBC/
```

Then follow the instructions in the official SPROUT repository.


## Data Source

We do **not claim ownership of the original datasets**. MoNuSeg, CPM17, and TNBC were released by their respective authors. This repository only provides reorganized/preprocessed versions of these datasets for reproducibility and convenient use with SPROUT.

## SPROUT Citation

If you use these preprocessed datasets together with SPROUT, please consider citing:

```bibtex
@inproceedings{zhang2026sprout,
  title={Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting},
  author={Wen Zhang and Qin Ren and Wenjing Liu and Haibin Ling and Chenyu You},
  booktitle={International Conference on Machine Learning},
  year={2026}
}
```

## License

The preprocessing and organization provided in this repository are intended to support reproducibility of the SPROUT project. The original datasets remain subject to their respective licenses and terms of use.

	---
	license: other
	task_categories:
	- image-segmentation
	tags:
	- pathology
	- nuclei-segmentation
	- medical-imaging
	- MoNuSeg
	- CPM17
	- TNBC
	pretty_name: SPROUT Preprocessed Datasets
	---

	# SPROUT Preprocessed Datasets

	This repository provides the preprocessed datasets used in SPROUT:

	> Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting
	> ICML 2026

	Official code repository: https://github.com/Y-Research-SBU/SPROUT

	## Datasets

	The repository contains preprocessed versions of the following publicly available nuclear segmentation datasets:

	* MoNuSeg
	* CPM17
	* TNBC

	The datasets have been reorganized and preprocessed to match the data format expected by the SPROUT codebase.

	## Directory Structure

	The dataset follows the structure used by SPROUT:

	```text
	MoNuSeg/
	├── train/
	│ ├── annotations/
	│ ├── images/
	│ ├── instances/
	│ ├── semantics/
	│ ├── png/
	│ └── train.txt
	└── test/
	├── annotations/
	├── images/
	├── instances/
	├── semantics/
	├── png/
	└── test.txt

	cpm17/
	...

	TNBC/
	...
	```

	## Usage

	Download or clone the dataset and place the dataset folders under the `data/` directory of the SPROUT repository:

	```text
	SPROUT/
	└── data/
	├── MoNuSeg/
	├── cpm17/
	└── TNBC/
	```

	Then follow the instructions in the official SPROUT repository.


	## Data Source

	We do not claim ownership of the original datasets. MoNuSeg, CPM17, and TNBC were released by their respective authors. This repository only provides reorganized/preprocessed versions of these datasets for reproducibility and convenient use with SPROUT.

	## SPROUT Citation

	If you use these preprocessed datasets together with SPROUT, please consider citing:

	```bibtex
	@inproceedings{zhang2026sprout,
	title={Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting},
	author={Wen Zhang and Qin Ren and Wenjing Liu and Haibin Ling and Chenyu You},
	booktitle={International Conference on Machine Learning},
	year={2026}
	}
	```

	## License

	The preprocessing and organization provided in this repository are intended to support reproducibility of the SPROUT project. The original datasets remain subject to their respective licenses and terms of use.