Buchumschlag

FECT: Classification of Breast Cancer Pathological Images Based on Fusion Features

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Hao, Jiacheng, Liu, Yiqing, Zeng, Siqi, He, Yonghong
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Image and Video Processing Computer Vision and Pattern Recognition
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Towards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sections
von: Ling, Xitong, et al.
Veröffentlicht: (2024)

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images
von: Luo, Yang, et al.
Veröffentlicht: (2025)

Patch Stitching Data Augmentation for Cancer Classification in Pathology Images
von: Wang, Jiamu, et al.
Veröffentlicht: (2025)

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
von: Tschuchnig, Maximilian, et al.
Veröffentlicht: (2025)

FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classification
von: Chakraborty, Bidisha, et al.
Veröffentlicht: (2024)

Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods
von: Abbasniya, Mohammad Reza, et al.
Veröffentlicht: (2022)

PathSeqSAM: Sequential Modeling for Pathology Image Segmentation with SAM2
von: Zhu, Mingyang, et al.
Veröffentlicht: (2025)

DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images
von: Lee, Ju Cheon, et al.
Veröffentlicht: (2024)

Using Multiparametric MRI with Optimized Synthetic Correlated Diffusion Imaging to Enhance Breast Cancer Pathologic Complete Response Prediction
von: Tai, Chi-en Amy, et al.
Veröffentlicht: (2024)

Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer
von: Pal, Surochita, et al.
Veröffentlicht: (2025)

CTI-Unet: Cascaded Threshold Integration for Improved U-Net Segmentation of Pathology Images
von: Zhu, Mingyang, et al.
Veröffentlicht: (2025)

Attention-Map Augmentation for Hypercomplex Breast Cancer Classification
von: Lopez, Eleonora, et al.
Veröffentlicht: (2023)

Breast Cancer Image Classification Method Based on Deep Transfer Learning
von: Wang, Weimin, et al.
Veröffentlicht: (2024)

SDF2Net: Shallow to Deep Feature Fusion Network for PolSAR Image Classification
von: Alkhatib, Mohammed Q., et al.
Veröffentlicht: (2024)

Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework
von: Afshin, Pouya, et al.
Veröffentlicht: (2025)

Classification of COVID-19 in Chest X-ray Images Using Fusion of Deep Features and LightGBM
von: Nasiri, Hamid, et al.
Veröffentlicht: (2022)

Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions
von: Luo, Luyang, et al.
Veröffentlicht: (2023)

Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound
von: Wu, Hong, et al.
Veröffentlicht: (2024)

FANCL: Feature-Guided Attention Network with Curriculum Learning for Brain Metastases Segmentation
von: Liu, Zijiang, et al.
Veröffentlicht: (2024)

A Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Images
von: Wu, Zhizhong, et al.
Veröffentlicht: (2024)

Vision-Language Model Based Multi-Expert Fusion for CT Image Classification
von: Bai, Jianfa, et al.
Veröffentlicht: (2026)

Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study
von: Eskandari, Sania, et al.
Veröffentlicht: (2024)

Exploring Kinetic Curves Features for the Classification of Benign and Malignant Breast Lesions in DCE-MRI
von: Li, Zixian, et al.
Veröffentlicht: (2024)

CLIP Based Region-Aware Feature Fusion for Automated BBPS Scoring in Colonoscopy Images
von: Fu, Yujia, et al.
Veröffentlicht: (2025)

DECT-based Space-Squeeze Method for Multi-Class Classification of Metastatic Lymph Nodes in Breast Cancer
von: Jiang, Hai, et al.
Veröffentlicht: (2025)

Deep Attention Unet: A Network Model with Global Feature Perception Ability
von: Li, Jiacheng
Veröffentlicht: (2023)

Optimizing Synthetic Correlated Diffusion Imaging for Breast Cancer Tumour Delineation
von: Tai, Chi-en Amy, et al.
Veröffentlicht: (2024)

To What Extent Do Token-Level Representations from Pathology Foundation Models Improve Dense Prediction?
von: Chen, Weiming, et al.
Veröffentlicht: (2026)

Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification
von: Hussain, Sadam, et al.
Veröffentlicht: (2024)

Transformers Fusion across Disjoint Samples for Hyperspectral Image Classification
von: Ahmad, Muhammad, et al.
Veröffentlicht: (2024)

LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
von: Zhang, Hantao, et al.
Veröffentlicht: (2024)

Dynamic Frequency Feature Fusion Network for Multi-Source Remote Sensing Data Classification
von: Zhao, Yikang, et al.
Veröffentlicht: (2025)

Advancing H&E-to-IHC Stain Translation in Breast Cancer: A Multi-Magnification and Attention-Based Approach
von: Qu, Linhao, et al.
Veröffentlicht: (2024)

Beyond H&E: Unlocking Pathological Insights with Polarization Imaging
von: Du, Yao, et al.
Veröffentlicht: (2025)

Enhancing Clinically Significant Prostate Cancer Prediction in T2-weighted Images through Transfer Learning from Breast Cancer
von: Tai, Chi-en Amy, et al.
Veröffentlicht: (2024)

HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis
von: Deng, Ruining, et al.
Veröffentlicht: (2024)

DSVTLA: Deep Swin Vision Transformer-Based Transfer Learning Architecture for Multi-Type Cancer Histopathological Cancer Image Classification
von: Khan, Muazzem Hussain, et al.
Veröffentlicht: (2026)

CEIMVEN: An Approach of Cutting Edge Implementation of Modified Versions of EfficientNet (V1-V2) Architecture for Breast Cancer Detection and Classification from Ultrasound Images
von: Banerjee, Sheekar, et al.
Veröffentlicht: (2023)

Deep Diversity-Enhanced Feature Representation of Hyperspectral Images
von: Hou, Jinhui, et al.
Veröffentlicht: (2023)

Radiomics-guided Multimodal Self-attention Network for Predicting Pathological Complete Response in Breast MRI
von: Kim, Jonghun, et al.
Veröffentlicht: (2024)