Breast-Mammography-Detection

Breast Tissue ROI Object Detection Model

Introduction:

The Breast Tissue ROI Object Detection Model is designed to locate regions of interest (ROIs) within mammographic images.

1. Purpose

The primary purpose of the Breast Tissue ROI Object Detection Model is to accurately and efficiently identify regions of interest in mammographic images. These regions typically contain suspicious lesions, calcifications, or abnormalities that require further examination to determine the presence of breast cancer.

2. Deep Learning Architecture:

This model is built on state-of-the-art deep learning architecture, leveraging Convolutional Neural Networks (CNNs) (with feature extraction). It utilizes a combination of convolutional layers, pooling layers, and fully connected layers to process mammographic images effectively.

• Developed by: https://github.com/RsGoksel
• Model type: Pytorch (.pt)

More Tools

• Repository: https://github.com/RsGoksel/Breast-Tissue-Cropper-Tools