Breast Tumour Classification
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Benchmarks
PCam
Most implemented
Densely Connected Convolutional Networks
BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
Rotation Equivariant CNNs for Digital Pathology
Rotation equivariant vector field networks
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
Virchow: A Million-Slide Digital Pathology Foundation Model
Papers
Attention-Map Augmentation for Hypercomplex Breast Cancer Classification
Breast cancer is the most widespread neoplasm among women and early detection of this disease is critical. Deep learning techniques have become of great interest to improve diagnostic performance. However, distinguishing…
Breast Cancer Histology Image ClassificationBreast Tumour ClassificationCancer ClassificationClassification+2Virchow: A Million-Slide Digital Pathology Foundation Model
The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnosis and treatment of cancer. Such applica…
Breast Tumour ClassificationCancer ClassificationmodelSelf-Supervised Learning+1Multi-View Hypercomplex Learning for Breast Cancer Screening
Traditionally, deep learning methods for breast cancer classification perform a single-view analysis. However, radiologists simultaneously analyze all four views that compose a mammography exam, owing to the correlations…
Breast Tumour ClassificationCancer ClassificationCancer-no cancer per breast classificationClassification+2Meta-repository of screening mammography classifiers
Artificial intelligence (AI) is showing promise in improving clinical diagnosis. In breast cancer screening, recent studies show that AI has the potential to improve early cancer diagnosis and reduce unnecessary workup. …
Breast Cancer DetectionBreast Tumour ClassificationMedical Image AnalysisAn End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. The large resolution makes WSIs infeasibl…
Breast Tumour ClassificationClassificationimage-classificationImage Classification+2BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening. The main contributions described here are threefold: 1) The design of an adv…
3D Medical Imaging SegmentationAutomatic Machine Learning Model SelectionBreast Cancer DetectionBreast Mass Segmentation In Whole Mammograms+6