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--- |
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license: apache-2.0 |
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task_categories: |
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- image-classification |
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language: |
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- en |
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tags: |
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- medical |
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- biology |
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--- |
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# Introduction |
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Our study includes 11 biomedical image classification datasets. Place all the datasets in one directory under `data` to ease management. The file structure looks like |
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``` |
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data/ |
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|–– BTMRI/ |
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|–– BUSI/ |
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|–– CHMNIST/ |
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|–– COVID_19/ |
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|–– CTKidney/ |
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|–– DermaMNIST/ |
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|–– KneeXray/ |
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|–– Kvasir/ |
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|–– LungColon/ |
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|–– OCTMNIST/ |
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|–– RETINA/ |
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``` |
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## Datasets Description |
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| **Modality** | **Organ(s)** | **Name** | **Classes** | **# train/val/test** | |
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|:---------------------------:|:-----------------:|:-------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:--------------------:| |
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| Computerized Tomography | Kidney | [CTKidney](https://www.kaggle.com/datasets/nazmul0087/ct-kidney-dataset-normal-cyst-tumor-and-stone)| Kidney Cyst, Kidney Stone, Kidney Tumor, Normal Kidney | 6221/2487/3738 | |
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| Dermatoscopy | Skin | [DermaMNIST](https://medmnist.com/) | Actinic Keratosis, Basal Cell Carcinoma, Benign Keratosis, Dermatofibroma, Melanocytic nevus, Melanoma, Vascular Lesion | 7007/1003/2005 | |
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| Endoscopy | Colon | [Kvasir](https://www.kaggle.com/datasets/abdallahwagih/kvasir-dataset-for-classification-and-segmentation)| Dyed Lifted Polyps, Normal Cecum, Esophagitis, Dyed Resection Margins, Normal Pylorus, Normal Z Line, Polyps, Ulcerative Colitis | 2000/800/1200 | |
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| Fundus Photography | Retina | [RETINA](https://www.kaggle.com/datasets/gunavenkatdoddi/eye-diseases-classification) | Cataract, Diabetic Retinopathy, Glaucoma, Normal Retina | 2108/841/1268 | |
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| Histopathology | Lung, Colon | [LC25000](https://www.kaggle.com/datasets/andrewmvd/lung-and-colon-cancer-histopathological-images)| Colon Adenocarcinoma, Colon Benign Tissue, Lung Adenocarcinoma, Lung Benign Tissue, Lung Squamous Cell Carcinoma | 12500/5000/7500 | |
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| Histopathology | Colorectal | [CHMNIST](https://www.kaggle.com/datasets/kmader/colorectal-histology-mnist) | Adipose Tissue, Complex Stroma, Debris, Empty Background, Immune Cells, Normal Mucosal Glands, Simple Stroma, Tumor Epithelium | 2496/1000/1504 | |
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| Magnetic Resonance Imaging | Brain | [BTMRI](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset) | Glioma Tumor, Meningioma Tumor, Normal Brain, Pituitary Tumor | 2854/1141/1717 | |
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| Optical Coherence Tomography| Retina | [OCTMNIST](https://medmnist.com/) | Choroidal Neovascularization, Drusen, Diabetic Macular Edema, Normal | 97477/10832/1000 | |
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| Ultrasound | Breast | [BUSI](https://www.kaggle.com/datasets/aryashah2k/breast-ultrasound-images-dataset) | Benign Tumors, Malignant Tumors, Normal Scans | 389/155/236 | |
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| X-Ray | Chest | [COVID-QU-Ex](https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database) | COVID-19, Lung Opacity, Normal Lungs, Viral Pneumonia | 10582/4232/6351 | |
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| X-Ray | Knee | [KneeXray](https://www.kaggle.com/datasets/shashwatwork/knee-osteoarthritis-dataset-with-severity) | No, Doubtful, Minimal, Moderate, and Severe Osteoarthritis | 5778/826/1656 | |
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### Download the datasets |
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All the datasets can be found [here](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/tree/main) on HuggingFace. Download each dataset seperately: |
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- <b>BTMRI</b> [[Drive](https://drive.google.com/file/d/1_lJLZRUmczqZqoN-dNqkAzGzmi4ONoU5/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/BTMRI.zip)] |
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- <b>BUSI</b> [[Drive](https://drive.google.com/file/d/1hB5M7wcAUTV9EtiYrijACoQ36R6VmQaa/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/BUSI.zip)] |
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- <b>CHMNIST</b> [[Drive](https://drive.google.com/file/d/1tyQiYQmqAGNaY4SCK_8U5vEbbaa1AD-g/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/CHMNIST.zip)] |
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- <b>COVID_19</b> [[Drive](https://drive.google.com/file/d/1zMLN5q5e_tmH-deSZQiY4Xq0M1EqCrML/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/COVID_19.zip)] |
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- <b>CTKidney</b> [[Drive](https://drive.google.com/file/d/1PBZ299k--mZL8JU7nhC1Wy8yEmlqmVDh/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/CTKidney.zip)] |
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- <b>DermaMNIST</b> [[Drive](https://drive.google.com/file/d/1Jxd1-DWljunRDZ8fY80dl5zUMefriQXt/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/DermaMNIST.zip)] |
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- <b>KneeXray</b> [[Drive](https://drive.google.com/file/d/1DBVraYJmxy2UcQ_nGLYvTB2reITOm453/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/KneeXray.zip)] |
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- <b>Kvasir</b> [[Drive](https://drive.google.com/file/d/1T_cqnNIjmGazNeg6gziarvCNWGsFEkRi/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/Kvasir.zip)] |
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- <b>LungColon</b> [[Drive](https://drive.google.com/file/d/1YIu5fqMXgyemisiL1L1HCvES2nVpCtun/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/LungColon.zip)] |
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- <b>OCTMNIST</b> [[Drive](https://drive.google.com/file/d/1mYZNWxbPxnnVvcwHQYybA8gdMzQAoOem/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/OCTMNIST.zip)] |
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- <b>RETINA</b> [[Drive](https://drive.google.com/file/d/18U-Gc22h5QryomNNzY4r4Qfrq52yf5EO/view?usp=sharing) | [HuggingFace](https://huggingface.co/datasets/TahaKoleilat/BiomedCoOp/resolve/main/RETINA.zip)] |
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After downloading each dataset, unzip and place each under its respective directory like the following |
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``` |
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BTMRI/ |
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|–– BTMRI/ |
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| |–– glioma_tumor/ |
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| |–– meningioma_tumor/ |
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| |–– normal_brain/ |
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| |–– pituitary_tumor/ |
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|–– split_BTMRI.json |
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``` |
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## Citation |
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If you use our work, please consider citing: |
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```bibtex |
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@article{koleilat2024biomedcoop, |
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title={BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models}, |
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author={Koleilat, Taha and Asgariandehkordi, Hojat and Rivaz, Hassan and Xiao, Yiming}, |
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journal={arXiv preprint arXiv:2411.15232}, |
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year={2024} |
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} |
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``` |
