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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

    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.

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    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.

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    Last Updated: May 14, 2026

    A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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    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
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    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
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    MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent

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  • 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.