14th European Congress on Digital Pathology
and the 5th Nordic Symposium on Digital Pathology
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29th May - 1st June, 2018, Helsinki, Finland
About the Conference
The primary goal is to bring together researchers, clinicians and industry working in the field of digital pathology, to present and discuss science, implementation of digital techniques and the latest advances in the field.
The congress theme is digital diagnostics and intelligence augmentation, with focus on artificial intelligence for pathology. The meeting also includes sessions on standards, quality management, clinical workflow integration, integrative pathology, translational research and precision medicine.
Conference History
This is the 14th European Congress on Digital Pathology.
The first was organized in Heidelberg (Germany, 1992) and the three most recent ones in Berlin,
Paris, Venice.
The conference is also the 5th Nordic Symposium on Digital Pathology,
the four previous being arranged in Linköping, Sweden.
About organizers
The main organizer is the Institute for molecular medicine Finland – FIMM,
University of Helsinki and endorsed by the European Society of Digital and Integrative Pathology.
Conference Speakers
The speakers are leading experts and researchers in the field of digital pathology, translational research, point-of-care
pathology and artificial intelligence applied to diagnostics.
Speakers
Michael Feldman
Professor, Vice Chairman Clinical Services, Pathology and Laboratory Medicine
University of Pennsylvania School of Medicine
Harry B. Burke
Professor of Medicine
F. Edward Hébert School of Medicine, Uniformed Services University
Daniel Racoceanu
Professor in Biomedical Image and Data Computing
Pontifical Catholic University of Peru
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Posters
01 1 Automated Ki67 “Pareto Hotspot” is an independent prognostic factor in breast cancer patients
Justinas Besusparis
National Centre of Pathology, Vilnius
02 2 A digital decision support tool to identify and classify lung cancer in human tissue samples
Nikolay Burlutskiy
Contextvision Ab
03 3 Wholeslide Validation of Automated H-Score Analysis of CEA-Expressing Tumor Cells in IHC Brightfield Imaging
Auranuch Lorsakul
Roche
04 4 Nuclei Detection: Inter-observer agreement and its impact on training a deep learning method
Henning Kost
Fraunhofer MEVIS
05 5 Validation of a Gleason Grading algorithm in prostate cancer biopsies
Agnieszka Krzyzanowska
Lund University
06 6 Deep learning tissue classification and fibrosis quantification in digital slides of Ductal Carcinoma in Situ(DCIS)
Zhaoyang Xu
Queen Mary University of London
07 7 Automated classification of non-small cell lung cancer histologic subtypes by deep learning
Ruben Casanova
University Hospital Zurich
08 8 Implementation of a digital pathology network in the northern part of The Netherlands
Jacko Duker
Umcg
09 9 Deep learning tissue classification in whole slides images of colorectal liver metastases after preoperative chemotherapy
Carlos Fernandez Moro
Department of Clinical Pathology/Cytology Karolinska University Hospital Huddinge
10 0 The importance of macro images for primary diagnosis with whole slide imaging
Filippo Fraggetta
Department of Pathology, Cannizzaro Hospital, Catania
11 11 Immunohistochemical fluoro-chromogenic staining and digital image analysis for accurate detection of PD-L1 in cytokeratin-positive NSCLC
Teppo Haapaniemi
Phhyky / Biositehisto / University of Tampere
12 2 Digital image analysis of HER2 in breast carcinoma: comparison with manual scoring and inter-platform agreement
Timco Koopman
University of Groningen, University Medical Center Groningen
14 4 Feasibility of Whole Slide Imaging in Hematopathology Practice: Experience with 707 International Telepathology Consultation Cases
Joshua Pantanowitz
University of Pittsburgh Medical Center
15 5 Correlation of Ki67 in Breast Cancer Biopsies and Surgical Specimens Using Image Analysis Techniques
David Pilutti
University of Udine
16 6 Morphometric assessment of intratumoral stroma changes in gastric carcinoma
Iancu-Emil Plesea
University of Medicine and Pharmacy "Carol Davila"
16 6 Embedded Deep Features for Classification of Breast Cancer Histology Images
Navid Alemi Koohbanani
University of Warwick
17 7 Considering the z-axis – control data created with digital image analysis on a next-generation Tissue Microarray (ngTMA®)
Inti Zlobec
18 8 Detection and grading of carcinoma ductal in situ by using structural features
Germán Corredor
Universidad Nacional de Colombia
19 9 Application of social communication networks in the continuing education of health professionals
Rodrigo Ugalde Herrá
Hospital Universitario Central de Asturias
20 0 Digital Diagnostics for Quantitative Evaluation of Proliferation Marker Ki-67 in Breast Cancer
Larisa Volkova
Immanuel Kant Baltic Federal Iniversity
21 1 Experience of Digital Pathology Applications in a Diagnostic Pathology Laboratory
Meral Üner
Yozgat City Hospital
22 2 Multi-Centre Raman Spectroscopy in Oesophageal Cancer Pathology Classification
Martin Isabelle
Renishaw Plc
23 3 A multiplexing imaging instrument with reagents for digital pathology employing novel up-converting nanoparticles
Anders Sjögren
Lumito Ab
24 4 Web application for pathology training using a low cost platform and annotated whole slide images
Paula Toro
Universidad Nacional de Colombia
25 5 A deep-learning algorithm to determine liver fat content in non-alcoholic fatty liver disease in humans.
Laura Ahtiainen
University of Helsinki
27 7 AI based Identification and Quantification of Growth Patterns in Lung Adenocarcinoma
Muhammad Shaban
Tissue Image Analytics Lab, Department of Computer Science, University of Warwick
28 8 Separating tissue and stain information using deep learning for increased generalization ability
Ida Arvidsson
Lund University
29 9 Accurate prostate glandular segmentation, a key to successful automatic grading and prognostication of prostate cancer
Christophe Avenel
Cadess Medical Ab
30 0 Deep convolutional neural network-based method for quantification of the pancreatic β-cell mass in mice
Tatiana Danilova
University of Helsinki
31 1 Automated slide screening for the diagnosis of breast cancer metastases in lymphnodes
Gianluca Gerard
32 2 A Multi-Task Deep Convolutional Network for Nuclei Segmentation
Simon Graham
University of Warwick
33 3 Automated quantification of steatosis: spatial heterogeneity matters
André Homeyer
Fraunhofer Mevis
35 5 Working methods for end-to-end development of automated assistants in pathology
Martin Lindvall
Sectra AB
36 6 On Quantifying the Role of Tumour Infiltrating Lymphocytes in Head and Neck Squamous Cell Carcinoma
Anna Lisowska
Warwick University
37 7 A Deep Learning Approach to Semantic Segmentation of Epidermal Tissue in Whole Slide Histopathological Images
Kay Raymond Oskal
International Research Institute of Stavanger
38 8 Implementation of Neural Networks for studies of brain pathology in Parkinson´s disease
Ilmari Parkkinen
University of Helsinki
39 9 HER2 Control-Aware Automatic Diagnosis Tool based on Deep Learning
Anibal Pedraza
VISILAB Research Group, University of Castilla la Mancha
40 0 Detection of β Cells in Immunohistochemical (IHC) Stained
Mouse Pancreatic Tissue
Talha Qaiser
University of Warwick
42 2 Preliminary study of stromal compartment of prostate cancer through fractal dimension
Mircea-sebastian Serbanescu
University of Medicine and Pharmacy of Craiova
43 3 Context Aware Deep Learning in Computational Pathology
Muhammad Shaban
University of Warwick
44 4 Deep learning for quantification of tall cells in papillary thyroid carcinoma
Sebastian Stenman
Institute for Molecular Medicine Finland - FIMM
45 5 Multi-Scale Fusion for Semantic Segmentation on CRLM Tumour Border
Zhaoyang Xu
Queen Mary University of London
46 6 New Cytomine modules for user behavior analytics in digital pathology
Raphaël Marée
University of Liège
47 7 Digital Microscopy in Modern Training of Clinical Pathology
Larisa Volkova
Immanuel Kant Baltic Federal Iniversity
49 9 Open source Piwigo as collaborative platform for effective review of histopathological annotations from digital slides.
Zhaoyang Xu
Queen Mary University of London
50 0 Quality Assurance and Local Regions for Whole Slide Image Registration
Leslie Solorzano
Uppsala University
51 1 Use of open communication platforms for diagnosis in Pathology
Rodrigo Ugalde Herrá
Hospital Universitario Central de Asturias
52 2 Telepathology in the Grand-Duchy of Luxembourg. Integrating a network of Hospitals with a central laboratory
Daniel Val
Laboratoire National de Santé
53 3 Chemotherapeutic response prediction in high-grade serous ovarian cancer using histopathological image analysis
Valeria Ariotta
Hautaniemi Lab, University of Helsinki
54 4 Cytologic immune cell-based risk score for patients with malignant pleural effusions
Chengguang Wu
University Hospital Zurich
55 5 Molecular tissue characterisation with mass spectrometry imaging: data analysis and visualisation
Judith Fonville
PAMM Laboratories
56 6 Heterogeneity analysis of patient-derived xenografts to optimize analysis of immune infiltrates in preclinical oncoimmunology research
Anne Grote
Hanover Medical School
57 7 Assessment of predictive biomarkers in cancer tissues using micro-immunohistochemistry followed by DNA sequencing
Anne-Laure Leblond
Institut für Klinische Pathologie und Molekular Pathologie
58 8 A digital pathology approach to evaluate the prognostic role of CAF-1/p60 in OSCC
Francesco Merolla
University of Molise - Department of Medicine and Health Sciences
60 0 Predicting prostate cancer progression using a network of bivariate prognostic models
Guenter Schmidt
Definiens AG
61 1 Digital image analysis of tumour associated macrophages in HER2 positive breast carcinoma
Mieke Zwager
UMCG