Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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

TrCN-HDC: Enhancing patient security with graphical authentication and cloud-assisted cardiac monitoring.

Computer methods and programs in biomedicine·2026
Same author

Efficacy of Injectable Platelet-Rich Fibrin for Interdental Papilla Reconstruction Compared With Connective Tissue Grafts: A Randomized Controlled Clinical Trial.

Cureus·2026
Same author

Association of Papillary Thyroid Carcinoma with GIST-a Case Series.

Indian journal of surgical oncology·2020
Same author

Does the Anatomy of the Transected Pancreatic Neck Influence Post Whipple's Operation Pancreatic Fistula?

Indian journal of surgical oncology·2019
Same author

Mesenteric fibromatosis (desmoid tumour) - a rare case report.

Journal of clinical and diagnostic research : JCDR·2015
Same author

Myoepithelial carcinoma of the breast.

Journal of clinical and diagnostic research : JCDR·2013

Related Experiment Video

Updated: Jun 9, 2025

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies
04:25

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

Published on: December 15, 2023

2.3K

Parallel-way: Multi-modality-based brain tumor segmentation using parallel capsule network.

Santhosh Kumar S1, Sasirekha S P1, Santhosh R1

  • 1Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, India.

Electromagnetic Biology and Medicine
|October 29, 2024
PubMed
Summary

This study introduces the Parallel-Way framework for enhanced brain tumor segmentation using MRI and PET imaging. The novel approach improves accuracy and overcomes limitations in current diagnostic tools.

Keywords:
MRI & PETTumor segmentationdeep neural networkfeature selection and twin transformerimage fusion

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

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

Published on: November 30, 2022

2.7K
Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
09:53

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

7.2K

Related Experiment Videos

Last Updated: Jun 9, 2025

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies
04:25

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

Published on: December 15, 2023

2.3K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

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

Published on: November 30, 2022

2.7K
Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
09:53

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

7.2K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence

Background:

  • Brain tumor diagnosis is challenging due to aberrant cell growth and difficulties in accurate segmentation from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans.
  • Limited sensitivity at boundary pixels and inadequacy of current fusion-based strategies hinder precise tumor localization and size determination.

Purpose of the Study:

  • To develop an advanced framework, Parallel-Way, for improving brain tumor segmentation accuracy by integrating MRI and PET data.
  • To overcome the limitations of existing segmentation methods, particularly at challenging boundary regions.

Main Methods:

  • Image quality enhancement using Improved Kalman Filter (IKF), Expectation Maximization (EM), and Improved Vibe Algorithm (IVib).
  • Multi-modality image fusion via Dual-Tree Complex Wavelet Transform (DTWCT).
  • Feature extraction using Advanced Capsule Network (ACN) and dimensionality reduction via Multi-objective Diverse Evolution-based selection, followed by segmentation using Twin Vision Transformer with dual attention.

Main Results:

  • The Parallel-Way framework demonstrated heightened model performance in brain tumor segmentation.
  • Evaluation metrics including accuracy, sensitivity, specificity, F1-Score, and AUC showed superiority over existing methodologies.

Conclusions:

  • The Parallel-Way framework offers a superior approach to brain tumor segmentation by effectively integrating multi-modal imaging data.
  • This advancement holds significant potential for improving the accuracy and efficacy of brain tumor diagnosis and treatment planning.