BreakHist Dataset contains histopathological images of eight types of breast cancer, including four benign cancer and for malignant cancer. In this project, I have trained and fined tuned many of the existing CNN models to get over 80% accuracy in multi-class classification.
🔬 Detecção Histopatológica de Câncer a partir de imagens disponibilizadas pelos datasets PatchCamelyon (PCam) e Breast Cancer Histopathological Dataset (BreakHis) e a partir de dados tabulares (Breast Cancer Wisconsin Diagnostic Dataset).
Use Breakhis dataset
Breast Cancer H&E classification of Images and Image Generation
A curated repository for the BreakHis Breast Cancer Histopathological Database, including folder structure, magnification levels, and class information for binary and multiclass classification tasks.
Exploratory analysis and visualization of a breast cancer histopathology image dataset, including binary and multiclass classification structures across multiple magnification levels.
Binary classification of breast cancer histopathology images (Benign vs Malignant) using an improved CNN on the BreakHis dataset - 88.24% test accuracy.
Add a description, image, and links to the breakhist-dataset topic page so that developers can more easily learn about it.
To associate your repository with the breakhist-dataset topic, visit your repo's landing page and select "manage topics."