Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Han, Martel, Anne L. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Attend what matters: Leveraging vision foundational models for breast cancer classification using mammograms
by: Sanghvi, Samyak, et al.
Published: (2026)
by: Sanghvi, Samyak, et al.
Published: (2026)
Computer Aided Detection and Classification of mammograms using Convolutional Neural Network
by: Ishaq, Kashif, et al.
Published: (2024)
by: Ishaq, Kashif, et al.
Published: (2024)
The LongiMam model for improved breast cancer risk prediction using longitudinal mammograms
by: Rakez, Manel, et al.
Published: (2025)
by: Rakez, Manel, et al.
Published: (2025)
A generalizable 3D framework and model for self-supervised learning in medical imaging
by: Xu, Tony, et al.
Published: (2025)
by: Xu, Tony, et al.
Published: (2025)
Classification with 2-D Convolutional Neural Networks for breast cancer diagnosis
by: Sharma, Anuraganand, et al.
Published: (2020)
by: Sharma, Anuraganand, et al.
Published: (2020)
Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
by: Ghahfarokhi, Sepehr Salem, et al.
Published: (2024)
by: Ghahfarokhi, Sepehr Salem, et al.
Published: (2024)
Learning using privileged information for segmenting tumors on digital mammograms
by: Tzortzis, Ioannis N., et al.
Published: (2024)
by: Tzortzis, Ioannis N., et al.
Published: (2024)
A self-supervised learning approach to deep filter banks for texture recognition
by: Florindo, Joao B., et al.
Published: (2026)
by: Florindo, Joao B., et al.
Published: (2026)
On depth prediction for autonomous driving using self-supervised learning
by: Boulahbal, Houssem
Published: (2024)
by: Boulahbal, Houssem
Published: (2024)
CoSwin: Convolution Enhanced Hierarchical Shifted Window Attention For Small-Scale Vision
by: Khadka, Puskal, et al.
Published: (2025)
by: Khadka, Puskal, et al.
Published: (2025)
Scaling up self-supervised learning for improved surgical foundation models
by: Jaspers, Tim J. M., et al.
Published: (2025)
by: Jaspers, Tim J. M., et al.
Published: (2025)
DB SwinT: A Dual-Branch Swin Transformer Network for Road Extraction in Optical Remote Sensing Imagery
by: He, Zongyang, et al.
Published: (2026)
by: He, Zongyang, et al.
Published: (2026)
Learning with less: label-efficient land cover classification at very high spatial resolution using self-supervised deep learning
by: Hester, Dakota, et al.
Published: (2025)
by: Hester, Dakota, et al.
Published: (2025)
DeTurb: Atmospheric Turbulence Mitigation with Deformable 3D Convolutions and 3D Swin Transformers
by: Zou, Zhicheng, et al.
Published: (2024)
by: Zou, Zhicheng, et al.
Published: (2024)
EA-Swin: An Embedding-Agnostic Swin Transformer for AI-Generated Video Detection
by: Mai, Hung, et al.
Published: (2026)
by: Mai, Hung, et al.
Published: (2026)
DarSwin: Distortion Aware Radial Swin Transformer
by: Athwale, Akshaya, et al.
Published: (2023)
by: Athwale, Akshaya, et al.
Published: (2023)
Multimodal self-supervised learning for lesion localization
by: Yang, Hao, et al.
Published: (2024)
by: Yang, Hao, et al.
Published: (2024)
Robust infrared small target detection using self-supervised and a contrario paradigms
by: Ciocarlan, Alina, et al.
Published: (2024)
by: Ciocarlan, Alina, et al.
Published: (2024)
Classifying Deepfakes Using Swin Transformers
by: Xi, Aprille J., et al.
Published: (2025)
by: Xi, Aprille J., et al.
Published: (2025)
Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers
by: Haftlang, Morteza Kiani, et al.
Published: (2025)
by: Haftlang, Morteza Kiani, et al.
Published: (2025)
SparseSwin: Swin Transformer with Sparse Transformer Block
by: Pinasthika, Krisna, et al.
Published: (2023)
by: Pinasthika, Krisna, et al.
Published: (2023)
Breast Cancer Detection from Multi-View Screening Mammograms with Visual Prompt Tuning
by: Chen, Han, et al.
Published: (2025)
by: Chen, Han, et al.
Published: (2025)
MV-Swin-T: Mammogram Classification with Multi-view Swin Transformer
by: Sarker, Sushmita, et al.
Published: (2024)
by: Sarker, Sushmita, et al.
Published: (2024)
Hybrid deep convolution model for lung cancer detection with transfer learning
by: Saxena, Sugandha, et al.
Published: (2025)
by: Saxena, Sugandha, et al.
Published: (2025)
Graph Neural Networks for modelling breast biomechanical compression
by: Awwad, Hadeel, et al.
Published: (2024)
by: Awwad, Hadeel, et al.
Published: (2024)
Slice-wise quality assessment of high b-value breast DWI via deep learning-based artifact detection
by: Markale, Ameya, et al.
Published: (2026)
by: Markale, Ameya, et al.
Published: (2026)
Small Object Detection for Birds with Swin Transformer
by: Huo, Da, et al.
Published: (2025)
by: Huo, Da, et al.
Published: (2025)
Weed Detection using Convolutional Neural Network
by: Tripathi, Santosh Kumar, et al.
Published: (2025)
by: Tripathi, Santosh Kumar, et al.
Published: (2025)
SwinMamba: A hybrid local-global mamba framework for enhancing semantic segmentation of remotely sensed images
by: Zhu, Qinfeng, et al.
Published: (2025)
by: Zhu, Qinfeng, et al.
Published: (2025)
Defect detection using weakly supervised learning
by: Sevetlidis, Vasileios, et al.
Published: (2023)
by: Sevetlidis, Vasileios, et al.
Published: (2023)
Complex Swin Transformer for Accelerating Enhanced SMWI Reconstruction
by: Usman, Muhammad, et al.
Published: (2025)
by: Usman, Muhammad, et al.
Published: (2025)
Image Super-Resolution Reconstruction Network based on Enhanced Swin Transformer via Alternating Aggregation of Local-Global Features
by: Huang, Yuming, et al.
Published: (2023)
by: Huang, Yuming, et al.
Published: (2023)
Utilizing Grounded SAM for self-supervised frugal camouflaged human detection
by: Pijarowski, Matthias, et al.
Published: (2024)
by: Pijarowski, Matthias, et al.
Published: (2024)
Block Pruning for Enhanced Efficiency in Convolutional Neural Networks
by: Wu, Cheng-En, et al.
Published: (2023)
by: Wu, Cheng-En, et al.
Published: (2023)
SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions
by: Papkov, Mikhail, et al.
Published: (2023)
by: Papkov, Mikhail, et al.
Published: (2023)
Affine transformation estimation improves visual self-supervised learning
by: Torpey, David, et al.
Published: (2024)
by: Torpey, David, et al.
Published: (2024)
Sleep-stage efficient classification using a lightweight self-supervised model
by: Durães, Eldiane Borges dos Santos, et al.
Published: (2026)
by: Durães, Eldiane Borges dos Santos, et al.
Published: (2026)
The effect of variable labels on deep learning models trained to predict breast density
by: Squires, Steven, et al.
Published: (2022)
by: Squires, Steven, et al.
Published: (2022)
SAM-Swin: SAM-Driven Dual-Swin Transformers with Adaptive Lesion Enhancement for Laryngo-Pharyngeal Tumor Detection
by: Wei, Jia, et al.
Published: (2024)
by: Wei, Jia, et al.
Published: (2024)
DIAR: Deep Image Alignment and Reconstruction using Swin Transformers
by: Kwiatkowski, Monika, et al.
Published: (2023)
by: Kwiatkowski, Monika, et al.
Published: (2023)
Similar Items
-
Attend what matters: Leveraging vision foundational models for breast cancer classification using mammograms
by: Sanghvi, Samyak, et al.
Published: (2026) -
Computer Aided Detection and Classification of mammograms using Convolutional Neural Network
by: Ishaq, Kashif, et al.
Published: (2024) -
The LongiMam model for improved breast cancer risk prediction using longitudinal mammograms
by: Rakez, Manel, et al.
Published: (2025) -
A generalizable 3D framework and model for self-supervised learning in medical imaging
by: Xu, Tony, et al.
Published: (2025) -
Classification with 2-D Convolutional Neural Networks for breast cancer diagnosis
by: Sharma, Anuraganand, et al.
Published: (2020)