whole slide images
266 papers with code • 0 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in whole slide images
Libraries
Use these libraries to find whole slide images models and implementations
CAMELYON16
PanNuke
CryoNuSeg
LKS
MITOS_WSI_CMC
Most implemented papers
PanNuke Dataset Extension, Insights and Baselines
The emerging area of computational pathology (CPath) is ripe ground for the application of deep learning (DL) methods to healthcare due to the sheer volume of raw pixel data in whole-slide images (WSIs) of cancerous tissue slides.
FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification
quiil/falformer
•
•
Herein, we propose an efficient and effective slide-level classification model, named as FALFormer, that can process a WSI as a whole so as to fully exploit the relationship among the entire patches and to improve the classification performance.
Assessment of Cell Nuclei AI Foundation Models in Kidney Pathology
Among the evaluated models, CellViT demonstrated superior performance in segmenting nuclei in kidney pathology.
Deep Learning for Identifying Metastatic Breast Cancer
3dimaging/DeepLearningCamelyon
•
•
The International Symposium on Biomedical Imaging (ISBI) held a grand challenge to evaluate computational systems for the automated detection of metastatic breast cancer in whole slide images of sentinel lymph node biopsies.
AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification
dazhangyu123/aem
•
•
While existing methods to alleviate this issue introduce complex modules or processing steps, such as multiple-stage training and teacher-student distillation, this paper proposes a simple yet effective regularization: Attention Entropy Maximization (AEM).
Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
Additionally, we evaluated object detection methods on a novel data set of 17 completely annotated cytology whole slide images (WSI) containing 78, 047 hemosiderophages.
A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
The pipeline consists of fully convolutional regression-based nucleus detection, followed by per-cell focus selection, and CNN based classification.
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images
mahmoodlab/CLAM
•
•
CLAM is a general-purpose and adaptable method that can be used for a variety of different computational pathology tasks in both clinical and research settings.
EXACT: A collaboration toolset for algorithm-aided annotation of images with annotation version control
In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation.
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning
binli123/dsmil-wsi
•
•
CVPR 2021
We propose a MIL-based method for WSI classification and tumor detection that does not require localized annotations.
