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 Experiment Video

Updated: May 14, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
06:08

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

MT-SAM: A Mamba-Transformer Enhanced SAM with Prior-guided Prompting for Multi-modal Prostate Cancer Delineation.

Litao Zhao, Yuhan Zhang, Libiao Ji

    IEEE Transactions on Medical Imaging
    |May 12, 2026
    PubMed
    Summary
    This summary is machine-generated.

    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

    Oncological Outcomes of Different Managements of the Distal Ureter in Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma.

    European urology oncology·2026
    Same author

    Assessment of anatomical outcomes in the upper urinary tract following flexible ureteroscopy with flexible and navigable suction ureteral access sheath: 1-year results from a multicentre study.

    BJUI compass·2026
    Same author

    Spatially Characterized Aortic Proteome Reveals Novel Regional Signatures and Glucocorticoid Receptor/Dipeptidase 1 Axis in Diabetic Vasculopathy.

    MedComm·2026
    Same author

    The global flexible and navigable suction ureteral access sheaths (FANS) survey on utility, practices and future needs in flexible ureteroscopy: a EAU Endourology, PEARLS and IAU collaboration.

    World journal of urology·2026
    Same author

    Orcinol glucoside ameliorates pulmonary fibrosis by suppressing hyaluronic acid synthesis and macrophage M2 polarization via targeting hyaluronic acid synthase 2.

    International journal of molecular medicine·2026
    Same author

    Training and external validation of machine learning supervised prognostic models of upper tract urothelial cancer (UTUC) after nephroureterectomy.

    Scientific reports·2026
    Same journal

    MUST: Multi-style virtual staining with incomplete pairs.

    IEEE transactions on medical imaging·2026
    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
    See all related articles

    A new MT-SAM framework improves the accuracy of delineating clinically significant prostate cancer (csPCa) from bi-parametric MRI (bp-MRI). This AI-driven approach enhances feature extraction and guidance, leading to better cancer localization for treatment.

    Area of Science:

    • Medical Imaging
    • Artificial Intelligence
    • Oncology

    Background:

    • Bi-parametric MRI (bp-MRI) is crucial for localizing prostate cancer, but accurate delineation of clinically significant prostate cancer (csPCa) is challenging due to image complexity and variability.
    • Current methods rely heavily on experienced clinicians, making the process time-consuming and subjective.

    Purpose of the Study:

    • To develop an automated framework, MT-SAM, for accurate and efficient csPCa delineation from bp-MRI.
    • To enhance the Segment Anything Model (SAM) with advanced feature extraction and guided prompting for improved performance.

    Main Methods:

    • Proposed MT-SAM framework integrating a mamba-transformer network for multi-stage, multi-modal feature extraction from bp-MRI.
    • Implemented cross-mamba modules to fuse extracted features into the SAM encoder.

    More Related Videos

    Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
    09:11

    Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

    Published on: April 9, 2019

    MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent
    06:54

    MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent

    Published on: September 3, 2013

    Related Experiment Videos

    Last Updated: May 14, 2026

    A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
    06:08

    A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

    Published on: March 21, 2025

    Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
    09:11

    Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

    Published on: April 9, 2019

    MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent
    06:54

    MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent

    Published on: September 3, 2013

  • Introduced a prior-guided pyramid-mamba prompting strategy to focus model attention on target regions.

    • Main Results:

    • MT-SAM achieved significantly higher Dice scores compared to state-of-the-art methods, with improvements ranging from 5.6% to 34.1%.
    • The framework demonstrated robust performance on both public and private datasets.

    Conclusions:

    • MT-SAM offers a promising solution for automated and accurate csPCa delineation from bp-MRI.
    • The enhanced feature extraction and prompting strategies contribute to improved diagnostic precision and potentially better patient outcomes.