Breast Cancer Detection
28 papers with code • 4 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Breast Cancer Detection
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Datasets
BRACS
CBIS-DDSM
BCI
BreakHis
BreastClassifications4
Latest papers
A Study of Acquisition Functions for Medical Imaging Deep Active Learning
bonaventuredossou/ece526_course_project
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In this work, we show how active learning could be very effective in data scarcity situations, where obtaining labeled data (or annotation budget is very limited).
CEIMVEN: An Approach of Cutting Edge Implementation of Modified Versions of EfficientNet (V1-V2) Architecture for Breast Cancer Detection and Classification from Ultrasound Images
In this research, we focused mostly on our rigorous implementations and iterative result analysis of different cutting-edge modified versions of EfficientNet architectures namely EfficientNet-V1 (b0-b7) and EfficientNet-V2 (b0-b3) with ultrasound image, named as CEIMVEN.
Screening Mammography Breast Cancer Detection
chakrabortyde/rsna-breast-cancer
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Breast cancer is a leading cause of cancer-related deaths, but current programs are expensive and prone to false positives, leading to unnecessary follow-up and patient anxiety.
Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism
netherlands-cancer-institute/ce-mri
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DWIs with different b-values are fused to efficiently utilize the difference features of DWIs.
High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection.
Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods
The Inception-ResNet-v2 which has both residual and inception networks profits together has shown the best feature extraction capability in the case of breast cancer histopathology images among all tested CNNs.
A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images
joe1chief/windownormalizaion
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In this study, we present a novel normalization technique called window normalization (WIN) to improve the model generalization on heterogeneous medical images, which is a simple yet effective alternative to existing normalization methods.
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
bupt-ai-cz/BCI
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The evaluation of human epidermal growth factor receptor 2 (HER2) expression is essential to formulate a precise treatment for breast cancer.
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset
SainiManisha/VGGIN-Net
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IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022
In this paper, we have presented a novel deep neural network architecture involving transfer learning approach, formed by freezing and concatenating all the layers till block4 pool layer of VGG16 pre-trained model (at the lower level) with the layers of a randomly initialized naïve Inception block module (at the higher level).
Meta-repository of screening mammography classifiers
Artificial intelligence (AI) is showing promise in improving clinical diagnosis.
