Machine Learning

A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation

CFPNet-M

This repository contains the implementation of a novel light-weight real-time network (CFPNet-Medicine: CFPNet-M) to segment different types of biomedical images. It is a medical version of CFPNet, and the dataset we used from top to bottom are DRIVE, ISBI-2012, Infrared Breast, CVC-ClinicDB and ISIC 2018. The details of CFPNet-M and CFPNet can be found here respectively.

Infrared-Breast

ISIC2018

Cvc-ClinicDB

Architecture of CFPNet-M

CFP module

cfp-module

CFPNet-M

fig-3

Dataset

In this project, we test five datasets:

  • [x] Infrared Breast Dataset
  • [x] Endoscopy (CVC-ClinicDB)
  • [x] Electron Microscopy (ISBI-2012)
  • [x] Drive (Digital Retinal Image)
  • [x] Dermoscopy (ISIC-2018)

Usage

Prerequisities

The following dependencies are needed: