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--- |
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license: mit |
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--- |
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# FISH_spots Dataset |
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The manually verified in situ hybridization fluorescence images and point coordinate dataset. |
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This dataset contains images and annotations for the task of single-molecule fluorescence in situ hybridization (FISH) spot detection, supporting 2D, 3D, and simulated noisy data. The structure is designed for deep learning model development, training, and evaluation. |
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## Directory Structure |
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``` |
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FISH_spots/ |
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├── 2d/ |
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│ ├── csv/ |
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│ ├── image/ |
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│ ├── image_raw/ |
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│ └── meta.csv |
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├── 3d/ |
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│ ├── csv/ |
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│ ├── image/ |
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│ ├── meta_test.csv |
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│ └── meta_valid.csv |
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└── noise/ |
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├── csv/ |
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├── image/ |
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├── meta.csv |
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├── meta_test.csv |
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└── meta_valid.csv |
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``` |
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## Download |
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```bash |
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# Make sure you have git-lfs installed (https://git-lfs.com) |
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git lfs install |
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git clone https://huggingface.co/datasets/GangCaoLab/FISH_spots |
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``` |
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## Data Content and Annotation Format |
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- **image directory** |
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Contains 512×512 image patches used for training. The images are ready for use by deep learning models, in standard formats such as PNG or TIFF. |
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- **csv directory** |
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Stores CSV files containing annotated spot positions for each corresponding image patch. Each row records the coordinates and other metadata of detected or simulated spots. |
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- **meta*.csv** |
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`meta.csv`, provide global metadata. |
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## 2D Dataset |
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- Includes data used in the U-FISH publication, comprising both real experimental data and simulated data. |
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- Covers 7 different experimental sources, providing diversity (real and simulated conditions). |
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- Contains over 4,000 images and 160,000 annotated spot positions. |
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- Suitable for benchmarking model generalization and spot detection in varied scenarios. |
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## 3D Dataset |
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- Mainly generated via simulation, representing spot distributions under 3D imaging conditions. |
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- Provides 3D image patches and coordinate-based annotations. |
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- Includes `meta_test.csv` and `meta_valid.csv` for easy split management. |
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## Noise Dataset |
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- Contains simulated noisy images aimed at testing model robustness to noise. |
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- Structure mirrors the 3D dataset, with patches, annotations, and metadata files. |
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## Citation |
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If you use this dataset in your research, please cite the U-FISH paper and Dataset(DOI: https://doi.org/10.57967/hf/6150). |
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