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

DeepEVD: Integrating Epidemiological data into deep learning frameworks based on spatio-temporal feature learning for EVD forecasting.

Spatial and spatio-temporal epidemiology·2025

Same author

Medical images lossless recovery based on POB number system and image compression.

Multimedia tools and applications·2022

Same author

Bisdemethoxycurcumin Protection of Cardiomyocyte Mainly Depends on Nrf2/HO-1 Activation Mediated by the PI3K/AKT Pathway.

Chemical research in toxicology·2019

Same author

Endogenous HCN Channels Modulate the Firing Activity of Globus Pallidus Neurons in Parkinsonian Animals.

Frontiers in aging neuroscience·2019

Same author

An Integrated Approach to Characterize Intestinal Metabolites of Four Phenylethanoid Glycosides and Intestinal Microbe-Mediated Antioxidant Activity Evaluation <i>In Vitro</i> Using UHPLC-Q-Exactive High-Resolution Mass Spectrometry and a 1,1-Diphenyl-2-picrylhydrazyl-Based Assay.

Frontiers in pharmacology·2019

Same author

Association of Epigenetic Clock with Consensus Molecular Subtypes and Overall Survival of Colorectal Cancer.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2019

Same journal

BrainCL: Transformer-Based Brain Network Contrastive Learning with Multi-Order Topology and Salience Masking.

IEEE transactions on medical imaging·2026

Same journal

LLM-enhanced Neuron Segmentation and Reconstruction in Complex Mouse Brain Images.

IEEE transactions on medical imaging·2026

Same journal

Matrixed-Spectrum Decomposition Accelerated Linear Boltzmann Transport Equation Solver for Fast Scatter Correction in Multi-Spectral CT.

IEEE transactions on medical imaging·2026

Same journal

The Ritz Adjoint Method for MRI Pulse Design.

IEEE transactions on medical imaging·2026

Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026

Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 15, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

MDPNet: Multiscale Dynamic Polyp-Focus Network for Enhancing Medical Image Polyp Segmentation.

Alpha Alimamy Kamara, Shiwen He, Abdul Joseph Fofanah

IEEE Transactions on Medical Imaging

|July 14, 2025

Summary

This summary is machine-generated.

Precise polyp segmentation is key for early colorectal cancer (CRC) detection. A new multiscale dynamic polyp-focus network (MDPNet) significantly improves segmentation accuracy, aiding earlier diagnosis and treatment.

More Related Videos

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

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Sep 15, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

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

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Area of Science:

Medical imaging analysis
Computational oncology
Artificial intelligence in healthcare

Background:

Colorectal cancer (CRC) is a leading cause of cancer mortality in the US.
Early detection through precise polyp segmentation is critical for improving patient outcomes.
Current segmentation methods like UNet struggle with polyp variability and low contrast.

Purpose of the Study:

To develop an advanced deep learning model for accurate colorectal polyp segmentation.
To address limitations of existing methods in handling variations in polyp appearance and context.
To enhance the early detection capabilities for colorectal cancer.

Main Methods:

Introduction of the multiscale dynamic polyp-focus network (MDPNet).
Incorporation of three key modules: DPfocus, NMAP, and LMAP.
DPfocus for global dependencies, NMAP for feature aggregation, and LMAP for spatial representation.

Main Results:

MDPNet demonstrates superior performance in polyp segmentation across four public datasets.
Achieved 2-5% higher overall accuracy compared to state-of-the-art methods.
Effectively handles variations in polyp shape, size, and contrast.

Conclusions:

MDPNet significantly improves polyp segmentation accuracy.
The proposed method aids in the early detection and treatment of colorectal cancer.
Enhanced segmentation accuracy contributes to better patient survival rates.