license: cc0-1.0
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 1439568612
num_examples: 249300
- name: validation
num_bytes: 79756681.5
num_examples: 13850
- name: test
num_bytes: 80391648.6
num_examples: 13850
download_size: 1678110616
dataset_size: 1599716942.1
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
task_categories:
- image-classification
language:
- en
tags:
- medical imaging
- histopathology
- breast cancer
- classification
pretty_name: Breast Histopathology Images
size_categories:
- 10K<n<100K
Dataset Card for Breast Histopathology Images
Dataset Overview
Breast Histopathology Images is a dataset containing high-resolution images of breast cancer specimens, specifically focusing on Invasive Ductal Carcinoma (IDC). The dataset is used for developing models to automatically detect and grade the aggressiveness of breast cancer based on histopathological images.
Context
Invasive Ductal Carcinoma (IDC) is the most common subtype of breast cancer. Pathologists often need to identify regions containing IDC to assign an aggressiveness grade to whole mount samples. This dataset provides a collection of patches extracted from whole mount slides to assist in training models for automatic IDC detection and classification.
Content
- Images: 162 whole mount slide images of breast cancer specimens scanned at 40x magnification.
- Patches: 277,524 patches of size 50x50 pixels extracted from the whole mount images.
- IDC Negative: 198,738 patches
- IDC Positive: 78,786 patches
Version
This version of the dataset is pre-split into training, validation, and test sets, making it ready for immediate use in machine learning tasks without additional preprocessing.
Source
The dataset is sourced from Kaggle: Breast Histopathology Images on Kaggle
Usage
This dataset is useful for training and evaluating models for histopathological image classification, particularly in the detection of IDC in breast cancer samples.
License
The dataset is licensed under CC0-1.0, which allows for unrestricted use and distribution.