Skip to content

ahmedeqbal/MET-Net

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

This repository contains the original PyTorch implementation of the paper "Memory-efficient transformer network with feature fusion for breast tumor segmentation and classification task", which was published in the journal "Engineering Applications of Artificial Intelligence - Elsevier" with an impact factor of 8.0.

Proposed Architecture

Feature Fusion Block

Challenging Visual Results

Requirements

  • GPU: NVIDIA GeForce RTX 2060 SUPER
  • Python 3.9.7
  • PyTorch: 2.0.0
  • OpenCV: 4.6.0
  • Numpy: 1.22.3
  • Matplotlib: 3.5.1

Cite:

Please cite the following paper if you use the MET-Net architecture in your project:

Iqbal, A., & Sharif, M. (2023). Memory-efficient transformer network with feature fusion for breast tumor segmentation and classification task. Engineering Applications of Artificial Intelligence, Volume 127, Part B, January 2024, 107292. DOI: https://doi.org/10.1016/j.engappai.2023.107292

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published