Digital Pathology
15th European Congress, ECDP 2019, Warwick, UK, April 10–13, 2019, Proceedings
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21 Result(s)
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Korsuk Sirinukunwattana
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Article
Open AccessImage-based consensus molecular subty** in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy
The development of deep learning (DL) models to predict the consensus molecular subtypes (CMS) from histopathology images (imCMS) is a promising and cost-effective strategy to support patient stratification. H...
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Article
Open AccessCorrection: Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
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Article
Open AccessContinuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
The grading of fibrosis in myeloproliferative neoplasms (MPN) is an important component of disease classification, prognostication and monitoring. However, current fibrosis grading systems are only semi-quanti...
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Chapter and Conference Paper
Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies
Existing methods for interpretability of model predictions are largely based on technical insights and are not linked to clinical context. We use the question of predicting response to radiotherapy in colorect...
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Article
Open AccessAutomated quality assessment of large digitised histology cohorts by artificial intelligence
Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the ...
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Chapter and Conference Paper
Enhancing Local Context of Histology Features in Vision Transformers
Predicting complete response to radiotherapy in rectal cancer patients using deep learning approaches from morphological features extracted from histology biopsies provides a quick, low-cost and effective way ...
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Chapter and Conference Paper
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning
Previous efforts to learn histology features that correlate with specific genetic/molecular traits resort to tile-level multi-instance learning (MIL) which relies on a fixed pretrained model for feature extrac...
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Article
Open AccessTranscriptome and genome evolution during HER2-amplified breast neoplasia
The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are s...
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Article
Open AccessAssociations of reproductive breast cancer risk factors with breast tissue composition
We investigated the associations of reproductive factors with the percentage of epithelium, stroma, and fat tissue in benign breast biopsy samples.
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Chapter and Conference Paper
Improving Pathological Distribution Measurements with Bayesian Uncertainty
Deep learning assisted histopathology has the potential to extract reproducible and accurate measurements from digitised slides in a scalable fashion. A typical workflow of such analysis may involve instance s...
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Article
Open AccessPrecision immunoprofiling by image analysis and artificial intelligence
Clinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational path...
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Article
Open AccessAuthor Correction: Why rankings of biomedical image analysis competitions should be interpreted with care
In the original version of this Article the values in the rightmost column of Table 1 were inadvertently shifted relative to the other columns. This has now been corrected in the PDF and HTML versions of the A...
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Book and Conference Proceedings
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Article
Open AccessWhy rankings of biomedical image analysis competitions should be interpreted with care
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to th...
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Article
Open AccessNovel digital signatures of tissue phenotypes for predicting distant metastasis in colorectal cancer
Distant metastasis is the major cause of death in colorectal cancer (CRC). Patients at high risk of develo** distant metastasis could benefit from appropriate adjuvant and follow-up treatments if stratified ...
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Chapter and Conference Paper
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study
While challenging, the dense segmentation of histology images is a necessary first step to assess changes in tissue architecture and cellular morphology. Although specific convolutional neural network architec...
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Chapter and Conference Paper
How to Exploit Weaknesses in Biomedical Challenge Design and Organization
Since the first MICCAI grand challenge organized in 2007 in Brisbane, challenges have become an integral part of MICCAI conferences. In the meantime, challenge datasets have become widely recognized as interna...
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Article
Open AccessGlandular Morphometrics for Objective Grading of Colorectal Adenocarcinoma Histology Images
Determining the grade of colon cancer from tissue slides is a routine part of the pathological analysis. In the case of colorectal adenocarcinoma (CRA), grading is partly determined by morphology and degree of...
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Article
Open AccessRobust normalization protocols for multiplexed fluorescence bioimage analysis
study of map** and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to us...
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Chapter and Conference Paper
A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images
Detection of epithelial tumor nuclei in standard Hematoxylin & Eosin stained histology images is an essential step for the analysis of tissue architecture. The problem is quite challenging due to the high chro...
