Table 6 Comparison of the proposed model with state-of-the-art methods. The performance is evaluated using mean dice (mDice) and mean intersection over union (mIoU) scores across five benchmark datasets.

UNet¹⁸

MICCAI 2015

0.710

0.627

0.823

0.755

0.504

0.436

0.398

0.335

0.818

0.746

UNet++¹⁹

IEEE TMI 2018

0.707

0.624

0.794

0.729

0.482

0.408

0.401

0.344

0.821

0.743

PraNet²⁷

MICCAI 2020

0.871

0.797

0.899

0.849

0.712

0.640

0.628

0.567

0.898

0.840

ACSNet⁴⁸

MICCAI 2020

0.863

0.787

0.882

0.826

0.716

0.649

0.578

0.509

0.898

0.838

UACANet-S⁴⁹

ACMMM 2021

0.902

0.837

0.916

0.870

0.783

0.704

0.694

0.615

0.905

0.852

Polyp-PVT³⁰

arXiv 2021

0.900

0.833

0.937

0.889

0.808

0.727

0.787

0.706

0.917

0.864

BDG-Net⁵⁰

Med. Imaging 2022

0.897

0.828

0.909

0.859

0.792

0.719

0.764

0.685

0.904

0.853

CASCADE⁵²

WACV 2023

0.898

0.833

0.923

0.878

0.809

0.728

0.808

0.735

0.926

0.876

MEGANet⁵³

WACV 2024

0.887

0.818

0.930

0.885

0.781

0.706

0.789

0.709

0.911

0.859

EMCAD-B2⁵⁴

CVPR 2024

0.885

0.812

0.929

0.881

0.819

0.736

0.794

0.717

0.924

0.878

MedSAM⁵⁵

Nature Com 2024

0.870

0.798

0.867

0.803

0.734

0.651

0.687

0.604

0.862

0.795

SAM2-UNet⁵⁶

arXiv 2024

0.894

0.827

0.907

0.856

0.808

0.730

0.796

0.723

0.928

0.879

BiCoMA (ours)

Scientific Reports

0.908

0.841

0.941

0.899

0.821

0.744

0.810

0.728

0.929

0.883