RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification
The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis.
However, due to the large scale of WSIs and various sizes of the abnormal area, how to …
However, due to the large scale of WSIs and various sizes of the abnormal area, how to …
Dgmil: Distribution guided multiple instance learning for whole slide image classification
Abstract Multiple Instance Learning (MIL) is widely used in analyzing histopathological
Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data …
Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data …
Cluster-to-conquer: A framework for end-to-end multi-instance learning for whole slide image classification
Y Sharma, A Shrivastava, L Ehsan… - … Imaging with Deep …, 2021 - proceedings.mlr.press
In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use
of deep learning-based computer vision techniques for automated disease diagnosis …
of deep learning-based computer vision techniques for automated disease diagnosis …
Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification
Multiple instance learning (MIL) has been increasingly used in the classification of
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
Multiple instance learning with center embeddings for histopathology classification
P Chikontwe, M Kim, SJ Nam, H Go… - Medical Image Computing …, 2020 - Springer
Histopathology image analysis plays an important role in the treatment and diagnosis of
cancer. However, analysis of whole slide images (WSI) with deep learning is challenging …
cancer. However, analysis of whole slide images (WSI) with deep learning is challenging …
Transmil: Transformer based correlated multiple instance learning for whole slide image classification
Multiple instance learning (MIL) is a powerful tool to solve the weakly supervised
classification in whole slide image (WSI) based pathology diagnosis. However, the current …
classification in whole slide image (WSI) based pathology diagnosis. However, the current …
Accounting for dependencies in deep learning based multiple instance learning for whole slide imaging
Multiple instance learning (MIL) is a key algorithm for classification of whole slide images
(WSI). Histology WSIs can have billions of pixels, which create enormous computational and …
(WSI). Histology WSIs can have billions of pixels, which create enormous computational and …
DT-MIL: deformable transformer for multi-instance learning on histopathological image
Learning informative representations is crucial for classification and prediction tasks on
histopathological images. Due to the huge image size, whole-slide histopathological image …
histopathological images. Due to the huge image size, whole-slide histopathological image …
Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution
Multiple instance learning (MIL) is a typical weakly-supervised learning method where the
label is associated with a bag of instances instead of a single instance. Despite extensive …
label is associated with a bag of instances instead of a single instance. Despite extensive …
MuRCL: Multi-instance reinforcement contrastive learning for whole slide image classification
Multi-instance learning (MIL) is widely adop-ted for automatic whole slide image (WSI)
analysis and it usually consists of two stages, ie, instance feature extraction and feature …
analysis and it usually consists of two stages, ie, instance feature extraction and feature …