Automatic breast cancer grading in lymph nodes using a deep neural network

07/24/2017
by   Thomas Wollmann, et al.
0

The progression of breast cancer can be quantified in lymph node whole-slide images (WSIs). We describe a novel method for effectively performing classification of whole-slide images and patient level breast cancer grading. Our method utilises a deep neural network. The method performs classification on small patches and uses model averaging for boosting. In the first step, region of interest patches are determined and cropped automatically by color thresholding and then classified by the deep neural network. The classification results are used to determine a slide level class and for further aggregation to predict a patient level grade. Fast processing speed of our method enables high throughput image analysis.

READ FULL TEXT

page 2

page 3

research
11/19/2022

convoHER2: A Deep Neural Network for Multi-Stage Classification of HER2 Breast Cancer

Generally, human epidermal growth factor 2 (HER2) breast cancer is more ...
research
09/09/2019

Detection and Classification of Breast Cancer Metastates Based on U-Net

This paper presents U-net based breast cancer metastases detection and c...
research
05/03/2019

PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis

Automatic detection of cancer metastasis from whole slide images (WSIs) ...
research
08/15/2017

Sparse Inverse Covariance Estimation for High-throughput microRNA Sequencing Data in the Poisson Log-Normal Graphical Model

We introduce the Poisson Log-Normal Graphical Model for count data, and ...
research
02/01/2020

Multi-stream Faster RCNN for Mitosis Counting in Breast Cancer Images

Mitotic count is a commonly used method to assess the level of progressi...
research
12/28/2017

A Partially Supervised Bayesian Image Classification Model with Applications in Diagnosis of Sentinel Lymph Node Metastases in Breast Cancer

A method has been developed for the analysis of images of sentinel lymph...
research
03/09/2021

NaroNet: Objective-based learning of the tumor microenvironment from highly multiplexed immunostained images

We present NaroNet, a Machine Learning framework that integrates the mul...

Please sign up or login with your details

Forgot password? Click here to reset