AI-based pathology predicts origins for cancers of unknown primary - Nature
Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks - MICCAI 2021
Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset
MICCAI2020. "Multiple Instance Learning with Center Embeddings for Histopathology Image Classification"
The code for Kernel attention transformer (KAT)
[ESWA 2023] Implementation of DSCA: A Dual-stream Network with Cross-attention on Whole-Slide Image Pyramids for Cancer Prognosis
Breast Cancer Image Classification On WSI With Spatial Correlations https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
PathoPatcher is a Python project designed for accelerating Whole Slide Image Preprocessing, employing AI-based preprocessing techniques with features like annotation handling, color normalization, and configurable parameters
Python 3 Package for optimally sampling big images with texture-aware patchification based on SLIC superpixels. So Sleek !
Diagnosis of histologic growth patterns of lung cancer in digital slides using deep learning.
Given an image of cells from a WSI, identify the mitotic figures and return a mitotic index.
Algorithm for the Whole Slide Images registration.
Keras unet and then chromogen analysis for prostate histopathology images.
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