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Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

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BPCN: bilateral progressive compensation network for lung infection image segmentation.

Xiaoyan Wang¹, Baoqi Yang¹, Xiang Pan¹

¹Zhejiang University of Technology, Zhejiang Province, People's Republic of China.

Physics in Medicine and Biology

|December 29, 2022

Summary

This study introduces the Bilateral Progressive Compensation Network (BPCN) for improved lung infection segmentation. The BPCN enhances accuracy by preserving crucial low-level details often lost in current methods.

Keywords:

adaptive body-edge aggregation bilateral spatial-channel down-sampling complementary learning lung infection image segmentation progressive fusion

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Area of Science:

Medical Image Analysis
Computer Vision
Artificial Intelligence

Background:

Accurate lung infection segmentation is vital for disease understanding.
Existing methods struggle with varied lesion shapes/sizes due to loss of low-level details.

Purpose of the Study:

To develop a novel network, the Bilateral Progressive Compensation Network (BPCN), for enhanced lung lesion segmentation accuracy.
To improve segmentation by complementary learning of spatial and semantic features, preserving fine details.

Main Methods:

Proposed the Bilateral Progressive Compensation Network (BPCN) with two deep branches.
One branch focuses on multi-scale progressive fusion of region features.
The other branch uses flow-field based adaptive aggregation for detail features and bilateral spatial-channel down-sampling for hierarchical complementary features.

Main Results:

The BPCN effectively preserves low-level details crucial for segmenting varied lung infection areas.
Experimental results demonstrate superior performance compared to state-of-the-art methods on public datasets.
The network shows effectiveness with or without a pseudo-label training strategy.

Conclusions:

The Bilateral Progressive Compensation Network (BPCN) significantly improves lung infection segmentation accuracy.
The proposed method addresses limitations of current approaches by retaining fine details.
BPCN offers a promising advancement for autonomous lung illness understanding through medical image analysis.