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07/13/2022
Domain adaptation strategies for cancer-independent detection of lymph node metastases
Recently, large, high-quality public datasets have led to the developmen...
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12/01/2021
Automatic tumour segmentation in H E-stained whole-slide images of the pancreas
Pancreatic cancer will soon be the second leading cause of cancer-relate...
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04/12/2021
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
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06/05/2020
Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels
Prostate cancer is the most prevalent cancer among men in Western countr...
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02/11/2020
Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists
While the Gleason score is the most important prognostic marker for pros...
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11/11/2019
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images
Due to memory constraints on current hardware, most convolution neural n...
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10/23/2019
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Automated medical image segmentation plays a key role in quantitative re...
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07/18/2019
Automated Gleason Grading of Prostate Biopsies using Deep Learning
The Gleason score is the most important prognostic marker for prostate c...
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05/16/2019
Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification
Large amounts of unlabelled data are commonplace for many applications i...
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02/25/2019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Semantic segmentation of medical images aims to associate a pixel with a...
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02/18/2019
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
Stain variation is a phenomenon observed when distinct pathology laborat...
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11/07/2018
Neural Image Compression for Gigapixel Histopathology Image Analysis
We present Neural Image Compression (NIC), a method to reduce the size o...
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08/17/2018
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks
Manual counting of mitotic tumor cells in tissue sections constitutes on...
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08/17/2018
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard
Prostate cancer (PCa) is graded by pathologists by examining the archite...
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04/19/2018
Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders
We propose an unsupervised method using self-clustering convolutional ad...
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04/16/2018
Training convolutional neural networks with megapixel images
To train deep convolutional neural networks, the input data and the inte...
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03/14/2018
Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study
Aim: Early detection and correct diagnosis of lung cancer are the most i...
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05/10/2017
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
Automated classification of histopathological whole-slide images (WSI) o...
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03/17/2017
Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images
Tissue segmentation is an important pre-requisite for efficient and accu...
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10/16/2016