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

MC-LBTO: secure and resilient state-aware multi-controller framework with adaptive load balancing for SD-IoT performance optimization.

Scientific reports·2025

Same author

RAUM-GANs: a multi-layer GAN-enhanced framework for accurate multiple sclerosis lesion segmentation in MRI.

Scientific reports·2025

Same author

Poisonous Plant Prediction Using Explainable Deep Inherent Learning Model.

Sensors (Basel, Switzerland)·2025

Same author

Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging.

Discover oncology·2025

Same author

Menstrual cycle inspired latent diffusion model for image augmentation in energy production.

Scientific reports·2025

Same author

A dual GAN with identity blocks and pancreas-inspired loss for renewable energy optimization.

Scientific reports·2025

Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026

Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026

Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026

Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026

Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026

Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 3, 2025

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

Brain Tumor Segmentation Using Deep Capsule Network and Latent-Dynamic Conditional Random Fields.

Mahmoud Elmezain^1,2, Amena Mahmoud³, Diana T Mosa³

¹Computer Science Department, Faculty of Science, Tanta University, Tanta 31527, Egypt.

Journal of Imaging

|July 25, 2022

Summary

This summary is machine-generated.

This study presents an automated brain tumor segmentation method using deep capsule networks (CapsNet) and latent-dynamic conditional random fields (LDCRF). The novel approach achieves competitive performance against state-of-the-art methods on benchmark datasets.

Keywords:

brain tumor deep capsule network latent-dynamic condition random field medical image segmentation

More Related Videos

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

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Related Experiment Videos

Last Updated: Sep 3, 2025

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

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Area of Science:

Medical Imaging
Artificial Intelligence
Computational Neuroscience

Background:

Brain tumor segmentation is challenging due to significant biological variability.
Accurate segmentation is crucial for diagnosis, treatment planning, and monitoring.

Purpose of the Study:

To develop an automated and accurate brain tumor segmentation method.
To integrate deep capsule networks (CapsNet) with latent-dynamic conditional random fields (LDCRF) for enhanced segmentation.

Main Methods:

A three-stage process: pre-processing (N4ITK bias correction, intensity normalization), segmentation (CapsNet training on image patches, LDCRF-CapsNet learning from axial slices), and post-processing (thresholding, small region removal).

Main Results:

The proposed LDCRF-CapsNet method demonstrated superior performance.
The method achieved competitive results compared to state-of-the-art techniques on BRATS 2015 and BRATS 2021 datasets.

Conclusions:

The integrated CapsNet and LDCRF approach offers an effective solution for automated brain tumor segmentation.
This method shows promise for clinical applications requiring precise tumor delineation.