LGPNet: A dual-branch parallel network for cervical cell image classification

No abstract is available for this paper.

• Publication year

  2026

• Venue

  Biomedical Signal Processing and Control

• Publication date

  Unknown publication date

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1016/j.bspc.2025.109076
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Revolutionizing cervical cancer detection: a new optimized explainable artificial intelligence model

  2025cited by this paper
• SE-DeepLabV3+: Cervical Cell Segmentation and Classification Using a Novel SE-Based DeepLabV3+ and Ensemble Method

  2025cited by this paper
• Stacked CNN-based multichannel attention networks for Alzheimer disease detection

  2025cited by this paper
• CNN based method for classifying cervical cancer cells in pap smear images

  2025cited by this paper
• A CNN-Transformer Approach for Image-Text Multimodal Classification with Cross-Modal Feature Fusion

  2025cited by this paper
• 3DECNN: a novel method for segmentation of the diabetic retinopathy in retinal fundus images using 3D-edge CNN

  2025cited by this paper
• Optimized segmentation of overlapping cervical cells based on Mask2Former and denoising

  2025cited by this paper
• CerviTransX: Explainable Transformer - Based Cervical Cancer Classification

  2025cited by this paper
• Vision transformer-based model can optimize curative-intent treatment for patients with recurrent hepatocellular carcinoma

  2025cited by this paper
• Towards Improved Cervical Cancer Screening: Vision Transformer-Based Classification and Interpretability

  2025cited by this paper
• An automatic cervical cell classification model based on improved DenseNet121

  2025cited by this paper
• Explainable Artificial Intelligence Driven Segmentation for Cervical Cancer Screening

  2025cited by this paper
• CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy

  2025cited by this paper
• Counterfactual Bidirectional Co-Attention Transformer for Integrative Histology-Genomic Cancer Risk Stratification

  2025cited by this paper
• A Novel Local Binary Patterns-Based Approach and Proposed CNN Model to Diagnose Breast Cancer by Analyzing Histopathology Images

  2025cited by this paper
• Label credibility correction based on cell morphological differences for cervical cells classification

  2025cited by this paper
• MCTGCL: Mixed CNN–Transformer for Mars Hyperspectral Image Classification With Graph Contrastive Learning

  2025cited by this paper
• Vision Transformers for Low-Quality Histopathological Images: A Case Study on Squamous Cell Carcinoma Margin Classification

  2025cited by this paper
• Transformative Advances in Cervical Cancer Diagnosis Leveraging Colposcopy Imaging with ViT

  2024cited by this paper
• HiCervix: An Extensive Hierarchical Dataset and Benchmark for Cervical Cytology Classification

  2024cited by this paper
• Cnn-trans model: A parallel dual-branch network for fundus image classification

  2024cited by this paper
• CA-ViT: Contour-Guided and Augmented Vision Transformers to Enhance Glaucoma Classification Using Fundus Images

  2024cited by this paper
• A pathology foundation model for cancer diagnosis and prognosis prediction

  2024cited by this paper
• A precise machine learning model: Detecting cervical cancer using feature selection and explainable AI

  2024cited by this paper
• RI-ViT: A Multi-Scale Hybrid Method Based on Vision Transformer for Breast Cancer Detection in Histopathological Images

  2024cited by this paper
• Deep Learning-Enabled Integration of Histology and Transcriptomics for Tissue Spatial Profile Analysis

  2024cited by this paper
• DAC-UNet: Dual Attention CNN-Enhanced CswinUnet for Gastric Cancer Pathological Image Segmentation

  2024cited by this paper
• Spatial transcriptomics reveals unique metabolic profile and key oncogenic regulators of cervical squamous cell carcinoma

  2024cited by this paper
• A review of convolutional neural network based methods for medical image classification

  2024cited by this paper
• SAC-Net: Enhancing Spatiotemporal Aggregation in Cervical Histological Image Classification via Label-Efficient Weakly Supervised Learning

  2024cited by this paper
• CNAC-Seg: Effective segmentation for cervical nuclei in adherent cells and clusters via exploring gaps of receptive fields

  2024cited by this paper
• Deep integrated fusion of local and global features for cervical cell classification

  2024cited by this paper
• SCAC: A Semi-Supervised Learning Approach for Cervical Abnormal Cell Detection

  2024cited by this paper
• Towards a general-purpose foundation model for computational pathology

  2024cited by this paper
• Medical Image Classifications Using Convolutional Neural Networks: A Survey of Current Methods and Statistical Modeling of the Literature

  2024cited by this paper
• Interpretable Cervical Cell Classification: A Comparative Analysis

  2024cited by this paper
• A novel SpaSA based hyper-parameter optimized FCEDN with adaptive CNN classification for skin cancer detection

  2024cited by this paper
• CDAM-Net: Channel shuffle dual attention based multi-scale CNN for efficient glaucoma detection using fundus images

  2024cited by this paper
• Vision transformer promotes cancer diagnosis: A comprehensive review

  2024cited by this paper
• An efficient Fusion-Purification Network for Cervical pap-smear image classification

  2024cited by this paper
• Lightweight Low-Rank Adaptation Vision Transformer Framework for Cervical Cancer Detection and Cervix Type Classification

  2024cited by this paper
• SwinCNN: An Integrated Swin Transformer and CNN for Improved Breast Cancer Grade Classification

  2024cited by this paper
• HiDiffSeg: A hierarchical diffusion model for blood vessel segmentation in retinal fundus images

  2024cited by this paper
• SAM-IE: SAM-based image enhancement for facilitating medical image diagnosis with segmentation foundation model

  2024cited by this paper
• VTHSC-MIR: Vision Transformer Hashing with Supervised Contrastive learning based medical image retrieval

  2024cited by this paper
• EnsembleCAM: Unified Visualization for Explainable Cervical Cancer Identification

  2024cited by this paper
• Multi-Branch Instance Segmentation of Cervical Cells

  2024cited by this paper
• PhaseFIT: live-organoid phase-fluorescent image transformation via generative AI

  2023cited by this paper
• CervixFormer: A Multi-scale swin transformer-Based cervical pap-Smear WSI classification framework

  2023cited by this paper
• Artificial Intelligence in Cervical Cancer Screening and Diagnosis

  2022cited by this paper
• A Deep Neural Network for Cervical Cell Classification Based on Cytology Images

  2022cited by this paper
• CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron

  2022cited by this paper
• The Bethesda System for reporting cervical cytology

  2022cited by this paper
• Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

  2021cited by this paper
• Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response

  2021cited by this paper
• A fuzzy rank-based ensemble of CNN models for classification of cervical cytology

  2021cited by this paper
• WHO launches strategy to accelerate elimination of cervical cancer.

  2020cited by this paper
• Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

  2018cited by this paper
• Sipakmed: A New Dataset for Feature and Image Based Classification of Normal and Pathological Cervical Cells in Pap Smear Images

  2018cited by this paper
• Cervical Cancer: Prevention and Early Detection.

  2017cited by this paper
• Attention is All you Need

  2017cited by this paper
• ImageNet classification with deep convolutional neural networks

  2012cited by this paper

• No citing papers are available for this paper.