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The rise of ai language pathologists: Exploring two-level prompt learning for few-shot weakly-supervised whole slide image classification
This paper introduces the novel concept of few-shot weakly supervised learning for
pathology Whole Slide Image (WSI) classification, denoted as FSWC. A solution is proposed …
pathology Whole Slide Image (WSI) classification, denoted as FSWC. A solution is proposed …
Boosting whole slide image classification from the perspectives of distribution, correlation and magnification
Bag-based multiple instance learning (MIL) methods have become the mainstream for
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Boosting multiple instance learning models for whole slide image classification: A model-agnostic framework based on counterfactual inference
Multiple instance learning is an effective paradigm for whole slide image (WSI) classification,
where labels are only provided at the bag level. However, instance-level prediction is also …
where labels are only provided at the bag level. However, instance-level prediction is also …
MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning
M Han, L Qu, D Yang, X Zhang, X Wang… - ar** an instance-level classifier via weakly-supervised self-training for whole slide image classification
Abstract Background and Objective Pathology image classification is crucial in clinical
cancer diagnosis and computer-aided diagnosis. Whole Slide Image (WSI) classification is …
cancer diagnosis and computer-aided diagnosis. Whole Slide Image (WSI) classification is …
Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology
Human visual attention allows prior knowledge or expectations to influence visual
processing, allocating limited computational resources to only that part of the image that are …
processing, allocating limited computational resources to only that part of the image that are …