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Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations
While high-resolution pathology images lend themselves well to `data hun...
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SAFRON: Stitching Across the Frontier for Generating Colorectal Cancer Histology Images
Synthetic images can be used for the development and evaluation of deep ...
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NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy Images
Object Segmentation is an important step in the work-flow of computation...
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Multi-Task Learning in Histo-pathology for Widely Generalizable Model
In this work we show preliminary results of deep multi-task learning in ...
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Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
Histology images are inherently symmetric under rotation, where each ori...
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PanNuke Dataset Extension, Insights and Baselines
The emerging area of computational pathology (CPath) is ripe ground for ...
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Meta-SVDD: Probabilistic Meta-Learning for One-Class Classification in Cancer Histology Images
To train a robust deep learning model, one usually needs a balanced set ...
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NuClick: From Clicks in the Nuclei to Nuclear Boundaries
Best performing nuclear segmentation methods are based on deep learning ...
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CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images
Colorectal cancer (CRC) grading is typically carried out by assessing th...
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Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework
Nuclear segmentation in histology images is a challenging task due to si...
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XY Network for Nuclear Segmentation in Multi-Tissue Histology Images
Nuclear segmentation within Haematoxylin & Eosin stained histology image...
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Methods for Segmentation and Classification of Digital Microscopy Tissue Images
High-resolution microscopy images of tissue specimens provide detailed i...
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Leveraging Transfer Learning for Segmenting Lesions and their Attributes in Dermoscopy Images
Computer-aided diagnosis systems for classification of different type of...
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Nuclei Detection Using Mixture Density Networks
Nuclei detection is an important task in the histology domain as it is a...
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Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds
With multiple crowd gatherings of millions of people every year in event...
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Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection
Mitosis count is an important biomarker for prognosis of various cancers...
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Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
Tumor proliferation is an important biomarker indicative of the prognosi...
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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions
International challenges have become the standard for validation of biom...
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MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images
The analysis of glandular morphology within colon histopathology images ...
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Fast and Accurate Tumor Segmentation of Histology Images using Persistent Homology and Deep Convolutional Features
Tumor segmentation in whole-slide images of histology slides is an impor...
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Novel digital tissue phenotypic signatures of distant metastasis in colorectal cancer
Distant metastasis is the major cause of death in colorectal cancer (CRC...
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Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues
Evaluating expression of the Human epidermal growth factor receptor 2 (H...
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