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

Related Concept Videos

X-ray Imaging

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...

You might also read

Related Articles

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

Sort by

Same author

Solvent-Mediated Synthesis of Small-Sized Perovskite Quantum Dots for a Color-Enhanced Micro-LED Display.

ACS nano·2025

Same author

Fruit flies exploit behavioral fever as a defense strategy against parasitic insects.

Science advances·2025

Same author

Innovative cage-based technique for mouse urine collection.

Laboratory animals·2025

Same author

Comment on "Modified amplatz sheath with suction versus standard sheath in percutaneous nephrolithotomy for treating large renal stones > 2 cm: a prospective randomized trial".

World journal of urology·2025

Same author

Symbiotic bracovirus of a parasite modulate host ecdysis process.

Cellular and molecular life sciences : CMLS·2025

Same author

A symbiotic gene stimulates aggressive behavior favoring the survival of parasitized caterpillars.

Proceedings of the National Academy of Sciences of the United States of America·2025

Same journal

Serum vitamin D level and its association with vertigo frequency and severity in Meniere disease.

Scientific reports·2026

Same journal

PFA-Net: a physics-informed feature enhancement and attention network for interpretable bearing fault diagnosis under strong noise.

Scientific reports·2026

Same journal

Circulating inflammatory, redox, and apoptosis-related alterations in drug-naive idiopathic pulmonary fibrosis: an exploratory case-control study.

Scientific reports·2026

Same journal

A baseline-oriented dynamic aggregation approach for demand-side heterogeneous controllable resources.

Scientific reports·2026

Same journal

Temporal precision and accuracy in schizophrenia: an exploratory study.

Scientific reports·2026

Same journal

Prefrontal EEG spectral and nonlinear signatures of subthreshold depression during resting state and affectively valenced picture/video viewing: a participant-level analysis.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 6, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Weakly supervised chest X-ray abnormality localization with non-linear modulation and foreground control.

Tongyu Wang¹, Kuan Huang², Meng Xu³

¹School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China.

Scientific Reports

|November 25, 2024

Summary

This summary is machine-generated.

This study introduces a new weakly supervised object localization (WSOL) framework for chest X-ray abnormality detection, improving accuracy without manual bounding boxes. The VMamba-based model enhances localization by refining foreground predictions and feature maps.

Keywords:

Abnormality localization Chest X-ray Foreground control Non-linear modulation VMamba Weakly supervised learning

More Related Videos

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Published on: July 23, 2020

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

Related Experiment Videos

Last Updated: May 6, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Published on: July 23, 2020

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

Area of Science:

Medical Imaging Analysis
Artificial Intelligence in Radiology
Computer-Aided Diagnosis

Background:

Chest X-rays are crucial for diagnosing lung diseases, but manual analysis is time-consuming.
Automated chest X-ray abnormality localization aims to reduce radiologist workload.
Weakly supervised object localization (WSOL) reduces annotation burden by using image-level labels instead of bounding boxes.

Purpose of the Study:

To develop a novel WSOL framework for accurate chest X-ray abnormality localization.
To overcome limitations of existing WSOL methods, such as incomplete coverage and fragmentation.
To improve the efficiency and accuracy of automated analysis of chest X-rays.

Main Methods:

Proposed a VMamba-based WSOL framework for chest X-ray abnormality localization.
Integrated a non-linear modulation module to refine Foreground Prediction Maps (FPM) for better continuity.
Developed an FPM fusion module and a novel foreground control loss to enhance foreground-background separability.

Main Results:

The proposed method demonstrated superior performance compared to six state-of-the-art WSOL methods on NIH and RSNA datasets.
Evaluated robustness and applicability across three additional datasets with varying modalities and image quality.
Achieved improved localization accuracy and feature map refinement for better foreground identification.

Conclusions:

The novel WSOL framework effectively localizes chest X-ray abnormalities with only image-level annotations.
The integrated modules significantly enhance localization accuracy and robustness.
The method offers a promising solution for reducing radiologist workload in chest X-ray interpretation.