Cardiac Image Segmentation by Combining Frequency Domain Prior and Feature Enhancement

Method	mDice				mJC	mASD	mHD
Method	Average	MYO	RV	LV	mJC	mASD	mHD
FCN	87.65	86.57	83.51	92.87	0.78	0.59	3.06
U-Net	88.31	85.97	85.03	93.94	0.79	0.56	2.84
TransUNet	89.56	86.42	87.54	94.71	0.81	0.54	2.79
Swin-UNet	87.56	82.97	85.69	94.03	0.79	0.42	1.92
DNet	91.36	89.07	89.37	95.64	0.84	0.34	1.62

Table 2. Comparison of segmentation effects of different prior guided strategies
View table
Table 2. Comparison of segmentation effects of different prior guided strategies
Strategy mDice mJC mASD mHD
Canny 86.70 0.78 3.54 25.43
Sobel 89.40 0.82 0.48 2.42
Fourier 91.36 0.84 0.34 1.62

Table 3. Comparison of segmentation effects of different feature fusion enhancement strategies
View table
Table 3. Comparison of segmentation effects of different feature fusion enhancement strategies
Strategy mDice mJC mASD mHD
U-Net++ 89.43 0.81 0.44 2.33
RefineNet 90.19 0.83 0.54 3.26
DNet 91.36 0.84 0.34 1.62

Table 4. Results of ablation experiments
View table
Table 4. Results of ablation experiments
Method mDice mJC mASD mHD
DNet-PGN-FFEB 89.79 0.82 0.62 2.51
DNet-PGN 90.31 0.82 0.48 2.54
DNet-FFEB 90.05 0.83 0.55 2.20
DNet 91.36 0.84 0.34 1.62

Table 5. Results of prior feature concatenation
View table
Table 5. Results of prior feature concatenation
Method mDice mJC mASD mHD
not concatenated 87.41 0.78 0.53 2.63
concatenated 91.36 0.84 0.34 1.62

Table 6. Results of using local and global attention individually and in combination
View table
Table 6. Results of using local and global attention individually and in combination
Method mDice mJC mASD mHD
local attention 90.16 0.83 0.43 2.17
global attention 88.38 0.80 1.10 5.49
both 91.36 0.84 0.34 1.62

Table 7. Results of using different mask shapes
View table
Table 7. Results of using different mask shapes
Shape mDice mJC mASD mHD
round 91.36 0.84 0.34 1.62
square 90.89 0.83 0.30 1.23

Table 8. Results of different mask radii
View table
Table 8. Results of different mask radii
Radius mDice mJC mASD mHD
20 90.07 0.83 0.38 2.07
30 91.36 0.84 0.34 1.62
40 90.47 0.83 0.34 1.39

Tools

Get Citation

Copy Citation Text

Keyan Chen, Qiaohong Liu, Xiaoxiang Han, Yuanjie Lin, Weikun Zhang. Cardiac Image Segmentation by Combining Frequency Domain Prior and Feature Enhancement[J]. Laser & Optoelectronics Progress, 2024, 61(10): 1037005

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Digital Image Processing

Received: Jul. 31, 2023

Accepted: Oct. 25, 2023

Published Online: Apr. 29, 2024

The Author Email: Qiaohong Liu (hqllqh@163.com)

DOI:10.3788/LOP231800

CSTR:32186.14.LOP231800

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Comparison of segmentation effects of different methods on ACDC dataset

Table 1. Comparison of segmentation effects of different methods on ACDC dataset

Table 2. Comparison of segmentation effects of different prior guided strategies

Table 2. Comparison of segmentation effects of different prior guided strategies

Table 3. Comparison of segmentation effects of different feature fusion enhancement strategies

Table 3. Comparison of segmentation effects of different feature fusion enhancement strategies

Table 4. Results of ablation experiments

Table 4. Results of ablation experiments

Table 5. Results of prior feature concatenation

Table 5. Results of prior feature concatenation

Table 6. Results of using local and global attention individually and in combination

Table 6. Results of using local and global attention individually and in combination

Table 7. Results of using different mask shapes

Table 7. Results of using different mask shapes

Table 8. Results of different mask radii

Table 8. Results of different mask radii