MLFE‐UNet: Multi‐Level Feature Extraction Transformer‐Based UNet for Gastrointestinal Disease Segmentation

International Journal of Imaging Systems and Technology, Год журнала: 2025, Номер 35(1)

Опубликована: Янв. 1, 2025

ABSTRACT Accurately segmenting gastrointestinal (GI) disease regions from Wireless Capsule Endoscopy images is essential for clinical diagnosis and survival prediction. However, challenges arise due to similar intensity distributions, variable lesion shapes, fuzzy boundaries. In this paper, we propose MLFE‐UNet, an advanced fusion of CNN‐based transformers with UNet. Both the encoder decoder utilize a multi‐level feature extraction (MLFA) CNN‐Transformer‐based module. This module extracts features input data, considering both global dependencies local information. Furthermore, introduce spatial attention (MLSA) block that functions as bottleneck. It enhances network's ability handle complex structures overlapping in maps. The MLSA captures multiscale tokens channel perspective transmits them decoding path. A contextual stabilization follows each transition emulate zones facilitate segmentation guidelines at phase. To address high‐level semantic information, incorporate computationally efficient block. followed by skip connections, ensuring interaction highlighting important decoder. evaluate performance our proposed selected common GI diseases, specifically bleeding polyps. dice coefficient scores obtained MLFE‐UNet on MICCAI 2017 (Red lesion) CVC‐ClinicalDB data sets are 92.34% 88.37%, respectively.

Язык: Английский

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A Feature Enhancement Network Based on Image Partitioning in a Multi-Branch Encoder-Decoder Architecture

Knowledge-Based Systems, Год журнала: 2025, Номер 311, С. 113120 - 113120

Опубликована: Фев. 1, 2025

Язык: Английский

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GSAC-UFormer: Groupwise Self-Attention Convolutional Transformer-Based UNet for Medical Image Segmentation

Cognitive Computation, Год журнала: 2025, Номер 17(2)

Опубликована: Фев. 22, 2025

Язык: Английский

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MLFA-UNet: A Multi-Level Feature Assembly UNet for Medical Image Segmentation

Methods, Год журнала: 2024, Номер 232, С. 52 - 64

Опубликована: Окт. 30, 2024

Язык: Английский

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DMFC-UFormer: Depthwise multi-scale factorized convolution transformer-based UNet for medical image segmentation

Biomedical Signal Processing and Control, Год журнала: 2024, Номер 101, С. 107200 - 107200

Опубликована: Ноя. 26, 2024

Язык: Английский

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A segmentation network for generalized lesion extraction with semantic fusion of transformer with value vector enhancement

Expert Systems with Applications, Год журнала: 2024, Номер 266, С. 126098 - 126098

Опубликована: Дек. 10, 2024

Язык: Английский

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