Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features
Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the ori...
Saved in:
Main Authors: | Eman Magdy, Nourhan Zayed, Mahmoud Fakhr |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2015-01-01
|
Series: | International Journal of Biomedical Imaging |
Online Access: | http://dx.doi.org/10.1155/2015/230830 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
FM1-Editorial board
Published: (2025-01-01) -
Building Crack Detection Based on Digital Image Processing Technology and Multiscale Feature Analysis Automatic Detection Algorithm
by: Chenguang Liu
Published: (2022-01-01) -
FM-EDCSK系统性能分析
by: 仇洪冰, et al.
Published: (2005-01-01) -
Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification
by: Aili Wang, et al.
Published: (2025-01-01) -
A Novel FM-DCSK Secure Communication System
by: Gang Zhang, et al.
Published: (2015-01-01)