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1808.04277
Cited By
BACH: Grand Challenge on Breast Cancer Histology Images
13 August 2018
Guilherme Aresta
Teresa Araújo
S. Kwok
Sai Saketh Chennamsetty
P. MohammedSafwanK.
Alex Varghese
B. Marami
Marcel Prastawa
Monica Chan
M. Donovan
G. Fernandez
J. Zeineh
Matthias Kohl
C. Walz
Florian Ludwig
S. Braunewell
Maximilian Baust
Q. Vu
Minh Nguyen Nhat To
Eal Kim
J. T. Kwak
Sameh Galal
Veronica Sanchez-Freire
N. Brancati
Maria Frucci
D. Riccio
Yaqi Wang
Lingling Sun
Kaiqiang Ma
Jiannan Fang
Ismaël Koné
L. Boulmane
A. Campilho
C. Eloy
A. Polónia
Paulo Aguiar
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Papers citing
"BACH: Grand Challenge on Breast Cancer Histology Images"
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Title
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Efficient High-Resolution Deep Learning: A Survey
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FHIST: A Benchmark for Few-shot Classification of Histological Images
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Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images
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Understanding the impact of image and input resolution on deep digital pathology patch classifiers
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Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
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Bag of Visual Words (BoVW) with Deep Features -- Patch Classification Model for Limited Dataset of Breast Tumours
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Classification of Microscopy Images of Breast Tissue: Region Duplication based Self-Supervision vs. Off-the Shelf Deep Representations
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HistoKT: Cross Knowledge Transfer in Computational Pathology
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Stephen Yang
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André Pedersen
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Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
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MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification
Zakaria Senousy
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Probeable DARTS with Application to Computational Pathology
Sheyang Tang
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A Computer-Aided Diagnosis System for Breast Pathology: A Deep Learning Approach with Model Interpretability from Pathological Perspective
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Yongfang Wu
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Yu-Ling Hou
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Tao He
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Hierarchical Semantic Segmentation using Psychometric Learning
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A Survey on Graph-Based Deep Learning for Computational Histopathology
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A Systematic Collection of Medical Image Datasets for Deep Learning
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An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
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Robust Hypothesis Testing with Wasserstein Uncertainty Sets
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Rui Gao
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Prediction of lung and colon cancer through analysis of histopathological images by utilizing Pre-trained CNN models with visualization of class activation and saliency maps
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Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
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Hierarchical Graph Representations in Digital Pathology
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Machine Learning Methods for Histopathological Image Analysis: A Review
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S. Ataky
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A Petri Dish for Histopathology Image Analysis
Jerry W. Wei
A. Suriawinata
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Michael Baker
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Lorenzo Torresani
Jason W. Wei
Saeed Hassanpour
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Gigapixel Histopathological Image Analysis using Attention-based Neural Networks
N. Brancati
G. De Pietro
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Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms
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MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis
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Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema
Jérémy Scheurer
Claudio Ferrari
Luis Berenguer Todo Bom
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HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification
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Guillaume Jaume
Lauren Alisha Fernandes
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Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Saypraseuth Mounsaveng
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David Vazquez
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Visualization for Histopathology Images using Graph Convolutional Neural Networks
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Abhijeet Patil
Deepak Anand
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Distributionally Robust Weighted
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Liyan Xie
Minghe Zhang
Rui Gao
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Extending and Analyzing Self-Supervised Learning Across Domains
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