April 28, 2022Open Access

MMC-Net: Multi-modal network for cardiac MRI segmentation of ventricular structures, and myocardium

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Why the study?

Automatic segmentation of multi-modal CMRI scans is challenging due to variant intensity distribution and unclear boundaries between neighbouring tissues and other organs.

Population

Multi-modal CMRI scans from the MS-CMRSeg-2019 challenge and ACDC datasets

Comparison

MMC-Net vs other state-of-the-art models and existing approaches

Design

Deep learning model development and validation study

Authors

GCG. Jignesh ChowdaryStony Brook University PYPratheepan YogarajahUniversity of Ulster PCPriyanka ChaurasiaUniversity of Ulster

Discussion

Member takes

Implication

May aid research segmentation workflows; leaves open clinical validation before practice adoption.

Structured PICO

Population

Multi-modal Cardiac Magnetic Resonance Imaging (CMRI) scans from the publicly available MS-CMRSeg-2019 challenge dataset and ACDC dataset

Intervention

Multi-Modal Cardiac Network (MMC-Net) deep convolutional neural network model

Comparator

Other state-of-the-art models and existing approaches

Outcome

Segmentation performance of right ventricle (RV), left ventricle (LV), and left ventricular myocardium (LVM)surrogate

The proposed MMC-Net deep learning model improves automated segmentation of ventricular structures and myocardium on multi-modal cardiac MRI scans.

Cite This Study

Chowdary et al. (2022) studied this question.

synapsesocial.com/papers/6a7bf2b561c5163555c629fc https://doi.org/10.36227/techrxiv.19641180

View Full Paper

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MMC-Net: Multi-modal network for cardiac MRI segmentation of ventricular structures, and myocardium

Discussion

Member takes

Implication

Structured PICO

Cite This Study

MMC-Net: Multi-modal network for cardiac MRI segmentation of ventricular structures, and myocardium

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider