SegChaNet: A Novel Model for Lung Cancer Segmentation in CT Scans
Accurate lung tumor identification is crucial for radiation treatment planning. Due to the low contrast of the lung tumor in computed tomography (CT) images, segmentation of the tumor in CT images is challenging. This paper effectively integrates the U-Net with the channel attention module (CAM) to...
Saved in:
Main Author: | Mehmet Akif Cifci |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Applied Bionics and Biomechanics |
Online Access: | http://dx.doi.org/10.1155/2022/1139587 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
RenalSegNet: automated segmentation of renal tumor, veins, and arteries in contrast-enhanced CT scans
by: Rashid Khan, et al.
Published: (2025-01-01) -
Performance and Analysis of FCN, U-Net, and SegNet in Remote Sensing Image Segmentation Based on the LoveDA Dataset
by: Yang Shuhao
Published: (2025-01-01) -
HandSegNet: Hand segmentation using convolutional neural network for contactless palmprint recognition
by: Koichi Ito, et al.
Published: (2022-03-01) -
MitoSeg: Mitochondria segmentation tool
by: Faris Serdar Taşel, et al.
Published: (2025-05-01) -
Registration-Based Morphing of Active Contours for Segmentation of CT Scans
by: Yuan-Nan Young, et al.
Published: (2004-10-01)