cnn4brca
Image Segmentation Project
This project uses Convolutional Neural Networks (CNN) for image segmentation of breast cancer lesions.
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis
75 stars
10 watching
50 forks
Language: Python
last commit: over 7 years ago
Linked from 1 awesome list
mrgloom/awesome-semantic-segmentationRelated projects:
| Repository | Description | Stars |
|---|---|---|
 ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 426 |
 nyukat/breast_cancer_classifier | A Python-based deep learning model for breast cancer classification from mammography images | 843 |
 zhengpeng7/birefnet | This repository provides a software framework and implementation of a neural network model for high-resolution image segmentation tasks | 1,379 |
 abbypa/nnproject_deepmask | A deep learning implementation of an object segmentation algorithm. | 187 |
 preritj/segmentation | Deep learning models for semantic segmentation of images | 100 |
 zfturbo/zf_unet_224_pretrained_model | A pre-trained convolutional neural network model for image segmentation tasks. | 214 |
 simonkohl/probabilistic_unet | Reimplementation of a neural network model for conditional segmentation of ambiguous images | 546 |
 fabianbormann/tensorflow-deconvnet-segmentation | An implementation of a deep learning algorithm for image segmentation using convolutional neural networks | 220 |
 nv-tlabs/gscnn | This code implements a neural network architecture designed to perform semantic segmentation in computer vision tasks. | 920 |
 ibbm/cascaded-fcn | An implementation of a Cascaded Fully Convolutional Neural Network architecture for medical image segmentation | 304 |
| zfturbo/keras-mask-rcnn-for-open-images-2019-instance-segmentation | Provides pre-trained Mask R-CNN models and example code for instance segmentation on the Open Images Dataset | 56 |
 ternaus/iglovikov_segmentation | A deep learning-based semantic segmentation pipeline using the Catalyst framework. | 20 |
 openai/pixel-cnn | A generative model with tractable likelihood and easy sampling, allowing for efficient data generation. | 1,921 |
 zsdonghao/u-net-brain-tumor | This repository demonstrates how to train a U-Net neural network for brain tumor segmentation using medical imaging data. | 505 |
 tramac/fast-scnn-pytorch | A PyTorch implementation of a deep learning model for semantic segmentation tasks in computer vision. | 381 |