Automated breast nuclei feature extraction for segmentation in histopathology images using Deep-CNN-based gaussian mixture model and color optimization technique

This publication has 47 references indexed in Scilit:

• DLRFNet: deep learning with random forest network for classification and detection of malaria parasite in blood smear
  Multimedia Tools and Applications, 2024
• Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images
  Multimedia Tools and Applications, 2022
• Breast histopathological image analysis using image processing techniques for diagnostic purposes: A methodological review
  Journal of Medical Systems, 2021
• An SVM approach towards breast cancer classification from H&E-stained histopathology images based on integrated features
  Medical & Biological Engineering & Computing, 2021
• Content-based image retrieval algorithm for nuclei segmentation in histopathology images
  Multimedia Tools and Applications, 2020
• Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma
  International Journal of Cancer, 2020
• UNet++: A Nested U-Net Architecture for Medical Image Segmentation
  2018
• U-Net: Convolutional Networks for Biomedical Image Segmentation
  2015
• Visualizing and Understanding Convolutional Networks
  2014
• Snakes: Active contour models
  International Journal of Computer Vision, 1988