Skip to main content

A comprehensive dataset for lymphocyte image classification (B cells, T4 cells, and T8 cells).

Project description

LymphoMNIST

Introducing LymphoMNIST, a comprehensive dataset tailored for the nuanced classification of lymphocyte images, encompassing an extensive collection of approximately 80,000 high-resolution 64x64 images. This dataset meticulously categorizes lymphocytes into three primary classes: B cells, T4 cells, and T8 cells, thereby facilitating a focused study on these fundamental immune cell types. Designed with precision, LymphoMNIST stands out as a high-quality, MNIST-like repository of standardized biomedical imagery, purposefully curated to ensure immediate applicability without necessitating extensive background knowledge in biomedical imaging.

LymphoMNIST aims to bridge the gap in biomedical image analysis by providing a dataset that is not only vast in scale but also rich in detail, thereby supporting a wide array of research endeavors, from fundamental biological studies to advanced computational model development. This dataset is particularly curated to cater to a variety of classification challenges, ranging from straightforward binary classifications to more complex multi-class identifications, thereby offering an invaluable resource for both educational and research-based explorations in the fields of biomedical image analysis, computer vision, and machine learning.

By focusing exclusively on B, T4, and T8 lymphocyte cells at a high resolution, LymphoMNIST enables the detailed study and development of specialized models that can accurately distinguish between these cell types, a critical requirement in both clinical diagnostics and immunological research. Whether for academic purposes, algorithm benchmarking, or enhancing the capabilities of open-source and commercial AutoML tools, LymphoMNIST provides a foundational platform for innovation and advancement in the medical imaging domain.

File structure

LymphoMNIST is organized as follows for easy integration into your projects:

LymphoMNIST/
├── LymphoMNIST/
│   ├── __init__.py
│   ├── LymphoMNIST.py  # main class for loading the data
│   └── utils.py        # Additional utility functions for easier visualization
├── tests/
│   ├── __init__.py
│   └── test_LymphoMNIST.py  # Optional: tests for the package
├── setup.py
├── README.md
└── LICENSE

Getting Started with LymphoMNIST

Get up and running with the LymphoMNIST dataset in a few simple steps. This guide will walk you through installing necessary dependencies, setting up the LymphoMNIST package, and loading the dataset for use in your machine learning models.

Step 1: Install Dependencies

pip install torch torchvision Pillow numpy tqdm requests matplotlib

Step 2: Install LymphoMNIST package

pip install LymphoMNIST

Step 3: Check LymphoMNIST version

import LymphoMNIST as info
print(f"LymphoMNIST v{info.__version__} @ {info.HOMEPAGE}")

For a detailed tutorial on using LymphoMNIST, follow this Google Colab notebook.

Open In Colab

Built With

  • PyTorch
  • NumPy
  • Matplotlib
  • tqdm

License

Distributed under the Apache License. See LICENSE for more information.

License

Contact

Khayrul Islam - @LinkedIN - khayrulbuet13@alum.lehigh.edu

Project Link: LymphoMNIST



Acknowledgments

This project is funded by:

NSF

Release Note

Initial release: This is the first release of LymphoMNIST, marking the introduction of the dataset to the research community.

(back to top)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lymphomnist-1.0.tar.gz (53.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lymphomnist-1.0-py3-none-any.whl (17.4 kB view details)

Uploaded Python 3

File details

Details for the file lymphomnist-1.0.tar.gz.

File metadata

  • Download URL: lymphomnist-1.0.tar.gz
  • Upload date:
  • Size: 53.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for lymphomnist-1.0.tar.gz
Algorithm Hash digest
SHA256 c7ae26a4f84d795f5d226e174a44881f668271e30a7c2f7593ae78d57781dae4
MD5 e88fc8625be2f7c3efafa3970efd2849
BLAKE2b-256 d7dd52ba2001b95bb7be2b79ec5a231c0e00224e9a0689804e526b0aacc5a520

See more details on using hashes here.

File details

Details for the file lymphomnist-1.0-py3-none-any.whl.

File metadata

  • Download URL: lymphomnist-1.0-py3-none-any.whl
  • Upload date:
  • Size: 17.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for lymphomnist-1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 63f551c883a28f5d46409467294c943fdd2e6859fa192fd4e725c193e8f45381
MD5 7436aae48fb4f3b9d499ff52b3da4689
BLAKE2b-256 cceac52b4d2d7a32466f7aef06868df4775fa041a3ff10f623992a0b008d479f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page