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

You might also read

Related Articles

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

Sort by

Same author

Enhanced YOLOv8n-based steel surface defect detection using adaptive threshold focal loss, swin transformer, and a high-resolution detection head.

Scientific reports·2026

Same author

Molecular Mechanism of Baicalin in Ameliorating Chronic Pancreatitis: Insights From Network Pharmacology and Metabolomics.

Biomedical chromatography : BMC·2026

Same author

Metabolic syndrome necroptosis: disease implications and therapeutic targeting.

Journal of physiology and biochemistry·2026

Same author

IHDCP: Single Image Dehazing Using Inverted Haze Density Correction Prior.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Camptothecin Nanoformulations: Recent Advances in Preparation, Bioactivities, and Clinical Perspectives.

Annals of biomedical engineering·2026

Same author

Do government subsidies lead to TFP losses? A perspective on the formation of zombie firms.

PloS one·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: Jul 9, 2026

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

Semantic-aware breast tumors segmentation network.

Liang Chen¹, Ting Hu¹, Donghua Yu¹

¹Institute of Artificial Intelligence, Shaoxing University, Shaoxing City, 312000, People's Republic of China.

Scientific Reports

|July 6, 2026

Summary

This summary is machine-generated.

This study introduces a new AI network, the Semantic-aware Breast Tumors Segmentation Network (SBTSN), for more accurate breast cancer detection in ultrasound images. SBTSN improves tumor boundary identification, aiding early diagnosis and better patient outcomes.

More Related Videos

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Related Experiment Videos

Last Updated: Jul 9, 2026

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Area of Science:

Medical Imaging
Artificial Intelligence
Oncology

Background:

Breast cancer poses a significant health risk to women globally.
Early detection through ultrasound is crucial for improving survival rates.
Ultrasound images present challenges like low contrast and blurry boundaries, hindering accurate tumor segmentation.

Purpose of the Study:

To develop an advanced AI model for precise breast tumor segmentation in ultrasound images.
To address limitations of current methods in handling image quality issues and tumor variability.
To enhance the accuracy and efficiency of automated breast cancer detection.

Main Methods:

Proposed the Semantic-aware Breast Tumors Segmentation Network (SBTSN), a U-Net-based architecture.
Introduced a novel Semantic-aware Block (SAB) to refine tumor boundaries using semantic guidance.
Implemented dynamic attention mechanisms within the SAB to focus on relevant features and reduce noise.

Main Results:

SBTSN demonstrated superior performance over state-of-the-art models on BUSI and STU datasets.
Achieved high scores in Dice and Intersection over Union (IoU) segmentation metrics.
Effectively reduced missed detections in complex clinical scenarios, showing improved accuracy.

Conclusions:

The SBTSN offers a robust solution for accurate breast tumor segmentation in ultrasound imaging.
The novel SAB effectively enhances boundary refinement and feature discrimination.
SBTSN provides a balance of high accuracy and computational efficiency for clinical applications.