Skin Lesion Image Segmentation Algorithm Based on MC-UNet
Aiming at the situation of dermatoscopic images with fuzzy lesion boundaries, variable morphology and high similarity to background, this paper proposes a skin lesion segmentation algorithm that achieves higher segmentation accuracy by combining existing convolutional neural network methods. The alg...
Saved in:
Main Authors: | Guihua Yang, Bingxing Pan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10845775/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Measurement of Seed Cotton Color Using RGB Imaging and Color-Unet
by: Hao Li, et al.
Published: (2024-12-01) -
Automatic Segmentation of Abdominal Aortic Aneurysm From Computed Tomography Angiography Using a Patch-Based Dilated UNet Model
by: Merjulah Roby, et al.
Published: (2025-01-01) -
D2CBDAMAttUnet: Dual-Decoder Convolution Block Dual Attention Unet for Accurate Retinal Vessel Segmentation From Fundus Images
by: Vo Trong Quang Huy, et al.
Published: (2025-01-01) -
Thyroid Nodule Ultrasound Image Segmentation Based on Improved Swin Transformer
by: Yue Wu, et al.
Published: (2025-01-01) -
MUNet: a novel framework for accurate brain tumor segmentation combining UNet and mamba networks
by: Lijuan Yang, et al.
Published: (2025-01-01)