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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

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Plane-Wave Image Reconstruction With Hy-PCF: A Novel Hybrid CNN-Transformer for Progressive Cross-Domain Fusion.

Yanyan Yu, Tianli Wang, Yu Qiang

IEEE Transactions on Medical Imaging

|February 24, 2026

Summary

This study introduces Hy-PCF, a novel hybrid CNN-Transformer network for plane-wave imaging. It enhances image quality and frame rate, overcoming limitations of traditional methods for better clinical practice.

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Area of Science:

Medical imaging
Ultrasound technology
Artificial intelligence in healthcare

Background:

Plane-wave (PW) imaging offers high temporal resolution but suffers from poor focus.
Beamforming methods like Coherent Plane-Wave Compounding (CPWC) improve quality but reduce frame rates.
A need exists for advanced methods balancing image quality and temporal performance in PW imaging.

Purpose of the Study:

To develop a novel hybrid network for simultaneous channel data and single-angle PW image utilization in image reconstruction.
To address the trade-off between image quality and frame rate in PW imaging.
To introduce a new approach for enhanced ultrasound image reconstruction.

Main Methods:

Proposed a hybrid progressive cross-domain fusion CNN-Transformer network (Hy-PCF).
Designed a Sparse Cross-Attention Guided Information Perception (SCAIP) module.
Utilized single-angle PW images to guide information extraction from channel data.

Main Results:

Hy-PCF significantly outperformed the conventional Delay-and-Sum (DAS) beamforming method.
The proposed network achieved performance comparable to Coherent Plane-Wave Compounding (CPWC).
Experimental findings demonstrated superior image reconstruction quality.

Conclusions:

Hy-PCF offers a promising hybrid CNN-Transformer solution for PW imaging.
The network effectively enhances image quality while maintaining high frame rates.
This advancement is critical for improving clinical ultrasound practice.