The poster authors will be at their posters during the poster reception.
All information regarding the posters will be provided soon.

P 01 Serbanescu Mircea-Sebastian (Romania) et al.
Introducing ChatGPT to Image Classification for Histopathology
P 02 Zehra Talat (Pakistan)
Dawn of AI enabled digital pathology in developing world- From benefits to challenges and possible solutions
P 03 Joona Pohjonen (Finland) et al.
Augment like there’s no tomorrow: Consistently performing neural networks for medical imaging
P 04 Filomena Barreto (Portugal) et al.
Harry Potter: a AI tool for diagnostic purposes
P 05 Ruoyu Shi (Singapore) et al.
Three dimensional surface scanning of surgical specimens for potential incorporation into routine macroscopic examination workflow- a pilot study
P 06 Philippe Weitz (Sweden) et al.
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
P 09 Nicolas Nerrienet (France) et al.
End-to-end pipeline for automatic grading of IHC biomarkers
P 10 Nora Manstein (Germany) et al.
Integrating AI into pathologists' work life
P 11 Meredith Lodge (United States) et al.
Halo Breast AI: a Deep Learning Workflow for Clinical Scoring of HER2, ER, PR & Ki67 Immunohistochemistry (IHC) in Breast Cancer Tissue
P 12 Petr Kuritcyn (Germany) et al.
Uncertainty calibrated deep tissue classification in histopathology
P 13 Rita Sarkis (Switzerland) et al.
Evaluation of Bone Marrow Stromal Edema by quantitative digital pathology
P 14 Kathy Robinson (Australia) et al.
A longitudinal Australasian review of consultant driven synchronous large group pathology education using digital slides
P 15 Nazish Jaffar (Pakistan) et al.
Ki 67 Quantification by Digital Image-Based AI Software & Its Correlation with Eye Ball Method in Breast Cancer
P 16 Christian Gebbe (Germany) et al.
Uncertainty-guided iterative training of supervised deep learning algorithms for digital pathology
P 17 Hussein Naji (Germany) et al.
Automated Nuclei Segmentation of H&E and IHC stained Whole Slide Images of Diffuse Large B-Cell Lymphoma
P 18 Moritz Fuchs (Germany) et al.
Improving the Reliability of Deep Learning in Computational Pathology
P 19 Yiyu Hong (South Korea) et al.
Virtual cytokeratin and LCA staining of gastric carcinomas to classify tumor microenvironment
P 20 Maren Høibø (Norway) et al.
Segmentation of epithelial cells in hematoxylin and eosin-stained histopathological breast cancer slides
P 21 Vincenzo Della Mea (Italy) et al.
Teaching Digital Pathology to future laboratory technicians: the Udine experience
P 22 Adam Shephard (United Kingdom) et al.
A Fully Automated Pipeline for the Prediction of Malignant Transformation in Oral Epithelial Dysplasia
P 23 Mai Bui (Germany) et al.
Few-shot learning of domain-invariant networks for domain-agnostic nuclei instance segmentation
P 24 Leslie Solorzano (Sweden) et al.
Ensembles for improved detection of invasive breast cancer in histological images
P 25 Yanbo Feng (Sweden) et al.
Exploring CNN activation patterns associated with the size of cancerous area in histopathology image and its relationship with model feature maps
P 26 Srijay Deshpande (United Kingdom) et al.
Interactive Synthesis of Histology Images from Bespoke Cellular Layouts
P 27 Michaela Benz (Germany) et al.
P 28 Melanie Lubrano (France) et al.
Deep Learning Model for Grading Head and Neck Squamous Lesions with a Grade-Sensitive Confidence Measure
P 29 Swapnil Rane (India) et al.
Cancer Imaging Biobank(CAIB)-AI ready health data from India
P 30 Johanna Palacios Ball (Spain) et al.
¿Is DICOM really important? What we have learned during our digital transformation process
P 31 Oded Ben-David (Israel) et al.
Virtual stain-multiplexing CD68 for PD-L1 IHC 22C3 pharmDx scanned NSCLC tissue slides
P 32 Bhakti Baheti (United States) et al.
Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current clinical knowledge
P 33 Filippo Ugolini (Italy) et al.
Tumor infiltrating lymphocytes recognition in primary melanoma by deep learning convolutional neuronal network
P 34 Margaret Horton (United States) et al.
The reading paradigm: How the sequence and presentation of AI results to pathologists influences endpoints and outcomes
P 35 Pedro C. Neto (Portugal) et al.
To err or to say “I don't know"? A study on the usage of efficient mixed supervision with a rejection option to diagnose colorectal lesions on WSI
P 36 Masi Valkonen (Finland) et al.
ACROBAT 2023: Analysis of multi-stain WSI registration algorithms under domain shift
P 37 Krzysztof Krawczyk (Sweden) et al.
Upconversion nanoparticles as labels for histopathological tissue evaluation
P 38 Hammam M. AlGhamdi (United Kingdom) et al.
Towards pan-cancer histology image classification with knowledge distillation
P 39 Wan Siti Halimatul Munirah Wan Ahmad (Malaysia) et al.
Classification of Nasopharyngeal Cases using DenseNet Deep Learning Architecture
P 40 Wan Siti Halimatul Munirah Wan Ahmad (Malaysia) et al.
Whole Slide Image scoring using DenseNet for ER-IHC: in search of optimal configuration
P 41 German Sergei (Germany)
Characterization of chronic kidney diseases with Self-Supervised Learning techniques
P 42 Viktoryia Zakharava (Belarus) et al.
Triple-negative breast cancer: structure and morphological features of immunohistochemical subtypes
P 43 Nicolò Caldonazzi (Italy) et al.
Automatic detection of Lymph node metastasis: twenty years of evolution
P 44 Manahil Raza (United Kingdom) et al.
Is Stain Augmentation All You Need for Domain Generalization?
P 45 Nur Basak Ozer (The Netherlands) et al.
Intraoperative Cytological Diagnosis of Brain Tumors: A Preliminary Study Using Deep Learning Model
P 46 Elias Baumann (Switzerland) et al.
Mapping the tumor microenvironment: Deep learning-based quantification of eosinophils and lymphocytes for patient outcome prediction in colon cancer
P 47 Nazanin Mola (Norway)
Effect of stain normalization on estimation of kidney fibrosis with image analysis
P 48 Made Satria Wibawa (United Kingdom) et al.
Digital Markers of Tumour Infiltrating Lymphocytes Predict Locoregional Recurrence-Free Survival in Nasopharyngeal Carcinoma
P 49 Thomas R Leech (United Kingdom) et al.
PathLAKE Portal: A Hybrid Platform for Showcasing and Sharing PathLAKE Whole-Slide Images
P 50 Aleksandra Asaturova (Russia) et al.
Morphologic criteria and CD138-positive cells counting for chronic endometritis: manual versus AI-based algorithms
P 51 Emre Karakok (Turkey) et al.
A retrospective evaluation of artificial intelligence solution for prostate biopsies
P 52 Hatem A. Rashwan (Spain) et al.
The BosomShield project: an integrative approach to diagnosis and prognosis of breast cancer relapse based on radiologic / pathologic image biomarkers
P 53 Mario Parreno-Centeno (United Kingdom) et al.
A deep-learning framework to dissect histological age patterns of the breast tissue
P 54 Viktoryia Zakharava (Belarus) et al.
Expression of metalloproteinases in assessing the effectiveness of therapy in patients with aggressive periodontitis
P 55 Till Nicke (Germany) et al.
Multitask pretraining outperforms ImageNet in learning general representations in computational pathology
P 56 Philippe Weitz (Sweden) et al.
Stratipath Breast: Deep Learning-Based Risk Stratification of Intermediate Risk Breast Cancers
P 57 Laura Mairinoja (Finland) et al.
Quantifying micro- and macrovesicular steatosis in preclinical mouse models of NAFLD by a deep learning based image analysis of whole slide images
P 58 Chuer Zhang (United Kingdom) et al.
Multicentre and Prospective: Multiplying the complexity to evaluate the health economics of AI for prostate cancer
P 59 Iancu Emil Plesea (Romania) et al.
Age related remodeling of aortic diameter
P 60 Iancu Emil Plesea (Romania) et al.
Aortic diameter remodeling depending on patient’s cause of death
P 61 Julius Drachneris (Lithuania) et al.
Prediction of NMIPUC Relapse from Hematoxylin-Eosin Images using Deep Multiple Instance Learning in patients treated with BCG immunotherapy
P 62 Walter de Back (Germany) et al.
Improving the efficiency and robustness of phenotyping in multiplex immunofluorescence whole slide imaging
P 63 Kesi Xu (United Kingdom) et al.
Auto-NuClick: A dual-stage neural network for nuclear instance segmentation
P 64 Matteo Pozzi (Italy) et al.
Diffusion models for WSI generation: a synthetic step towards supporting sharing and mitigating imbalance
P 65 Rita Canas-Marques (Portugal) et al.
Fully Automated Artificial Intelligence Solution for Accurate HER2 IHC Scoring in Breast Cancer: Multi-Reader Study
P 66 Kajsa Ledesma Eriksson (Sweden) et al.
Semantic Segmentation of DCIS in Breast Cancer Histopathology Whole Slide Images with Deep Learning
P 67 Lia DePaula Oliveira (United States) et al.
Assessing Risk of Prostate Cancer Metastasis by Deep Learning in Surgically-Treated Patients
P 68 Eric Erak (United States) et al.
Deep Learning-Based Identification of Lymph Node Metastasis in Prostate Cancer
P 69 DR JAYA JAIN (India) et al.
Z stacking for WSI generation improves the TIL detections algorithm performance in Breast cancer cases
P 70 David Snead (United Kingdom) et al.
Multi-site validation of digital pathology for the routine reporting of histopathology samples
P 71 Christian Mate (Germany) et al.
On robustness and domain generalization of classification systems for leukocytes in peripheral Blood and Bone Marrow
P 72 Celine Degaillier (Belgium) et al.
Digital pathology - from clinic to research. The UZBrussel - VUB experience
P 73 E Kontsek (Hungary) et al.
Multivariate modelling of mid-infrared spectra of colorectal cancer
P 74 János Báskay (Hungary) et al.
Reconstructing 3D histological structures using machine learning (AI) algorithms
P 75 E Kontsek (Hungary) et al.
Colorectal cancer screening aided by AI