A deep learning based multiscale approach to segment cancer area in liver whole slide image

07/25/2020
by   Yanbo Feng, et al.
0

This paper addresses the problem of liver cancer segmentation in Whole Slide Image (WSI). We propose a multi-scale image processing method based on automatic end-to-end deep neural network algorithm for segmentation of cancer area. A seven-levels gaussian pyramid representation of the histopathological image was built to provide the texture information in different scales. In this work, several neural architectures were compared using the original image level for the training procedure. The proposed method is based on U-Net applied to seven levels of various resolutions (pyramidal subsumpling). The predictions in different levels are combined through a voting mechanism. The final segmentation result is generated at the original image level. Partial color normalization and weighted overlapping method were applied in preprocessing and prediction separately. The results show the effectiveness of the proposed multi-scales approach achieving better scores compared to the state-of-the-art.

READ FULL TEXT

page 2

page 6

page 7

page 8

research
05/13/2021

Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images

Multiple myeloma cancer is a type of blood cancer that happens when the ...
research
09/04/2023

FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation

This contribution presents a deep learning method for the segmentation o...
research
08/11/2021

Automatic Polyp Segmentation via Multi-scale Subtraction Network

More than 90% of colorectal cancer is gradually transformed from colorec...
research
04/21/2022

Multiscale Analysis for Improving Texture Classification

Information from an image occurs over multiple and distinct spatial scal...
research
08/09/2023

Assessing the performance of deep learning-based models for prostate cancer segmentation using uncertainty scores

This study focuses on comparing deep learning methods for the segmentati...
research
01/22/2019

Multi-Task Learning with a Fully Convolutional Network for Rectum and Rectal Cancer Segmentation

In a rectal cancer treatment planning, the location of rectum and rectal...
research
03/05/2017

Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images

Histopathological characterization of colorectal polyps is an important ...

Please sign up or login with your details

Forgot password? Click here to reset