LuminaAI/RCL-Breast-Cancer-Biopsy-7500

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Breast Cancer Histopathological Dataset (BreakHis)

Overview

This dataset contains histopathological images of breast cancer tissues, divided into two classes: benign and malignant. Each sample is stored in a separate image file, organized into respective class folders. The dataset is structured to be compatible with Lumina AI's Random Contrast Learning (RCL) algorithm via the PrismRCL application or API.

Dataset Structure

The dataset is organized into the following structure:

Breast_Cancer_Histopathological_Dataset/ train_data/ benign/ sample_0.png sample_1.png ... malignant/ sample_0.png sample_1.png ... test_data/ benign/ sample_0.png sample_1.png ... malignant/ sample_0.png sample_1.png ...

Note: All image file names must be unique across all class folders.

Features

• Image Data: Each file contains a histopathological image of breast cancer tissue.
• Classes: There are two classes, each represented by a separate folder based on the type of tissue (benign or malignant).

Usage (not pre-split; optimal parameters)

Here is an example of how to load the dataset using PrismRCL:

C:\PrismRCL\PrismRCL.exe fractal imaginary rclticks=15 boxdown=0 channelpick=4 data=C:\path\to\Breast_Cancer_Biopsy_7500 testsize=0.1 savemodel=C:\path\to\models\mymodel.classify log=C:\path\to\log_files stopwhendone```

Explanation:

• C:\PrismRCL\PrismRCL.exe: classification application
• chisquared: training evaluation method
• rclticks=15: RCL training parameter
• boxdown=0: RCL training parameter
• data=C:\path\to\Breast_Cancer_Histopathological_Dataset\train_data: path to training data
• testdata=C:\path\to\Breast_Cancer_Histopathological_Dataset\test_data: path to testing data
• savemodel=C:\path\to\models\mymodel.classify: path to save resulting model
• log=C:\path\to\log_files: path to logfiles
• stopwhendone: ends the PrismRCL session when training is done

License

This dataset is licensed under the Creative Commons Attribution 4.0 International License. See the LICENSE file for more details.

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Original Source

This dataset was originally sourced from the Breast Cancer Histopathological Database (BreakHis). You can find the original dataset and more information at:

BreakHis: Breast Cancer Histopathological Database

Please cite the original source if you use this dataset in your research or applications. The recommended citation is:

Spanhol, F. A., Oliveira, L. S., Petitjean, C., Heutte, L. (2016). A Dataset for Breast Cancer Histopathological Image Classification. IEEE Transactions on Biomedical Engineering (TBME), 63(7):1455-1462.

This citation ensures proper attribution to the original creators of the BreakHis dataset.

Additional Information

The data values have been prepared to ensure compatibility with PrismRCL. No normalization is required as of version 2.4.0.