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Table 4 comparisons with the state-of-the-art baselines on the isic-2018 dataset

From: EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation

Method

Year

mDice

mIoU

Recall

Precision

U-Net [5]

2015

0.6740

0.5490

0.7080

–

PraNet [48]

2020

0.8746

0.8023

0.9128

0.8759

MSRF-Net [41]

2021

0.8813

0.8325

0.8903

0.9267

DoubleU-Net [25]

2020

0.8962

0.8212

0.8780

0.9459

TransAttUnet_D [13]

2021

0.9014

0.8304

0.9042

0.9217

TransAttUnet_R [13]

2021

0.9074

0.8380

0.9093

0.9242

EG-TransUNet

–

0.9075

0.8441

0.9169

0.9165

  1. The “–” denotes the corresponding result is not provided. For each column, the best results are highlighted
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BMC Bioinformatics

ISSN: 1471-2105

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