Multi-Resolution CNN and Knowledge Transfer for Candidate Classification in Lung Nodule Detection
The automatic lung nodule detection system can facilitate the early screening of lung cancer and timely medical interventions. However, there still exist multiple nodule candidates produced by initial rough detection in this system, and how to determine authenticity is a key problem. As this work is...
Main Authors: | Wangxia Zuo, Fuqiang Zhou, Zuoxin Li, Lin Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8662660/ |
Similar Items
-
Lung Nodule Texture Detection and Classification Using 3D CNN
by: Ivan William Harsono
Published: (2019-10-01) -
Using a Noisy U-Net for Detecting Lung Nodule Candidates
by: Wenkai Huang, et al.
Published: (2019-01-01) -
Systematic review for lung cancer detection and lung nodule classification: Taxonomy, challenges, and recommendation future works
by: Jassim Mustafa Mohammed, et al.
Published: (2022-08-01) -
Multi-Level Cross Residual Network for Lung Nodule Classification
by: Juan Lyu, et al.
Published: (2020-05-01) -
Dense Convolutional Binary-Tree Networks for Lung Nodule Classification
by: Yijing Liu, et al.
Published: (2018-01-01)