DeepAI AI Chat
Log In Sign Up

Deep Transfer Convolutional Neural Network and Extreme Learning Machine for Lung Nodule Diagnosis on CT images

by   Xufeng Huang, et al.

Diagnosis of benign-malignant nodules in the lung on Computed Tomography (CT) images is critical for determining tumor level and reducing patient mortality. Deep learning-based diagnosis of nodules in lung CT images, however, is time-consuming and less accurate due to redundant structure and the lack of adequate training data. In this paper, a novel diagnosis method based on Deep Transfer Convolutional Neural Network (DTCNN) and Extreme Learning Machine (ELM) is explored, which merges the synergy of two algorithms to deal with benign-malignant nodules classification. An optimal DTCNN is first adopted to extract high level features of lung nodules, which has been trained with the ImageNet dataset beforehand. After that, an ELM classifier is further developed to classify benign and malignant lung nodules. Two datasets, including the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) public dataset and a private dataset from the First Affiliated Hospital of Guangzhou Medical University in China (FAH-GMU), have been conducted to verify the efficiency and effectiveness of the proposed approach. The experimental results show that our novel DTCNN-ELM model provides the most reliable results compared with current state-of-the-art methods.


page 3

page 5

page 8

page 10


An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

While deep learning methods are increasingly being applied to tasks such...

Deep Learning Neural Network for Lung Cancer Classification: Enhanced Optimization Function

Background and Purpose: Convolutional neural network is widely used for ...

Dual Windows Are Significant: Learning from Mediastinal Window and Focusing on Lung Window

Since the pandemic of COVID-19, several deep learning methods were propo...

Integrating Feature and Image Pyramid: A Lung Nodule Detector Learned in Curriculum Fashion

Lung nodules suffer large variation in size and appearance in CT images....

Faithful learning with sure data for lung nodule diagnosis

Recent evolution in deep learning has proven its value for CT-based lung...

Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks

Early diagnosis of pathological invasiveness of pulmonary adenocarcinoma...