Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jul 11, 2026

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules

Published on: October 13, 2023

Adaptive collaborative feature fusion and shape-aware optimization for multi-scale chest lesion detection.

Yubo Yuan^1,2, Chengkang Liu^1,2, Qingwen Feng^3,4

¹School of Information Engineering, Zhengzhou University of Science and Technology, Zhengzhou, 450064, China.

Scientific Reports

|June 12, 2026

Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A bicentric study on the application of dual energy CT for predicting hemorrhagic transformation post endovascular thrombectomy.

Scientific reports·2025

Same author

Cascade-targeting pH/ROS microneedles promote scarless diabetic wound healing by macrophage metaboimmune reprogramming.

Science advances·2025

Same author

Research Progress on Non-Destructive Testing Technology and Equipment for Poultry Eggshell Quality.

Foods (Basel, Switzerland)·2025

Same author

Fucoidan ameliorates rotenone-induced Parkinsonism in mice by regulating the microbiota-gut-brain axis.

International journal of biological macromolecules·2024

Same author

Reactive oxygen species-responsive polydopamine-PtCuTe nanoparticle-loaded microneedle system for promoting the healing of infected skin wounds.

Journal of controlled release : official journal of the Controlled Release Society·2024

Same author

Natural Exponential and Three-Dimensional Chaotic System.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2023

This summary is machine-generated.

This study introduces a novel multi-scale method for detecting chest lesions in X-rays, improving accuracy for small and irregular findings. The approach enhances early diagnosis and clinical decision-making for chest diseases.

Area of Science:

Medical Imaging
Artificial Intelligence
Radiology

Background:

Chest diseases are a leading cause of global mortality.
Accurate detection of chest lesions from X-rays is crucial for timely diagnosis.
Automated detection faces challenges with lesion variability and precise localization.

Purpose of the Study:

To develop an advanced multi-scale method for robust chest lesion detection.
To enhance the accuracy and localization of automated systems for complex X-ray images.
To improve the identification of small and irregularly shaped lesions.

Main Methods:

Proposed a multi-scale chest lesion detection method using adaptive collaborative feature fusion and shape-aware optimization.
Developed a Context-Embedded Feature Enhancement Network for global and local feature integration.

More Related Videos

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

Published on: February 9, 2024

Related Experiment Videos

Last Updated: Jul 11, 2026

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules

Published on: October 13, 2023

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

Published on: February 9, 2024

Introduced an Adaptive Feature Focusing Network for improved multi-scale feature representation.

Implemented a shape-aware optimization strategy with normalized Wasserstein distance and shape-weighted constraints.

Main Results:

Achieved a 6.3% increase in mean Average Precision (mAP) on the VinDr-CXR dataset.
Improved small-lesion detection by 6.4% mAP and mean recall by 8.6% on VinDr-CXR.
Demonstrated a 4.2% mAP and 7.8% mean recall improvement on the ChestX-ray8 dataset.

Conclusions:

The proposed method effectively addresses challenges in multi-scale chest lesion detection.
The approach shows significant improvements in accuracy and localization robustness.
The method exhibits strong generalization capabilities for diverse chest X-ray datasets.