The poster authors will be at their posters during the poster reception.
All information regarding the posters will be provided soon.
| P01 |
Brijdeep Singh (India) et al. Transforming Diagnostics Through Telepathology: Insights from a Tertiary Care Center of Excellence |
| P02 |
Oskar Thaeter (Germany) et al. Deep Learning–Based Fixation Type Prediction for Quality Assurance in Digital Pathology |
| P03 |
Hugo David Alfici (Argentina) et al. Use of Information Technologies in Pathologists in Argentina: A Long Road |
| P04 |
Joice Soliman (Toronto, ON Canada ) et al. Selecting High Throughput Scanners for Clinical Usage: A Multi-Center Institution Experience |
| P05 |
Blake Clarke (Toronto, ON Canada ) et al. Digital Pathology Implementation in A Multi-Site Hospital Network: The Devil is in the Details |
| P06 |
Florian Jaeckle (United Kingdom) et al. Interpretable Machine Learning based Detection of Coeliac Disease |
| P07 |
Alessio Fiorin (Spain) et al. Strengthening Tumour-Infiltrating Lymphocyte Scoring in Sequential Breast Cancer Slides Using Region of Interest Registration |
| P08 |
Van-Linh Le (France) et al. Predicting the EPClin score in HER2-negative luminal breast cancer from Whole Slide Images by using transformer-based model |
| P09 |
Chiara Frascarelli (Italy) et al. Deep Learning in Digital Cytopathology: Evaluating Whole-Slide Images for Thyroid FNA Classification |
| P10 |
Misgina Tsighe Hagos (Sweden) et al. Quantifying Aleatoric and Epistemic Model Uncertainty to Select Accurate Identifications of Lung Cancer |
| P11 |
Ruben Lucassen (The Netherlands) et al. Triaging Cutaneous Melanocytic Lesions using Artificial Intelligence |
| P12 |
Hassan Keshvarikhojasteh (The Netherlands) et al. GigaPath Foundation Model For Lymphovascular Invasion Detection in Breast Cancer |
| P13 |
Adam Shephard (UK) et al. AI-based Classification of Laryngeal Lesions and Lymphocytic Activity in Dysplasia |
| P14 |
Garazi Serna (Spain) et al. Immunohistochemistry to Hematoxylin and Eosin Transfer Learning for Artificial Intelligence-Guided Tumor and Immune Cell Recognition Model Development |
| P15 |
Hong Liu (Netherlands) et al. PathoPainter: Enhancing Tumor Segmentation in Histopathology with Inpainting-Based Augmentation |
| P16 |
Noriko Watanabe (Japan) et al. Artificial Intelligence Prediction of Medulloblastoma Recurrence from Pathological Images |
| P17 |
Chan Kwon Jung (Korea) et al. Spatial Transcriptomics and Digital Pathology-Based Biomarker Discovery in Anaplastic Thyroid Carcinoma Progression |
| P18 |
Yu Deok Choi (South Korea) et al. Comparison of artificial intelligence-assissted and manual quantification of PDL1 expression in non-small cell lung cancer |
| P19 |
Zahra Farshidrokh (Netherlands) et al. Wavelet Transform and U-Net Framework for Spectral Decomposition and Noise Reduction in In Vivo Magnetic Resonance Spectroscopy |
| P20 |
Youngseop Lee (Korea) et al. AI caption generation model for digital pathology in endoscopic histopathology |
| P21 |
Carmen van Dooijeweert (The Netherlands) et al. Broad implementation of AI for lymph node assessment: insights from a head-to-head comparison of two applications |
| P22 |
Maanvi Saikia (India) et al. Enhancing Medical Education through Digital Pathology: Development of Interactive e-Learning Modules under the National Medical College Network |
| P23 |
J.E. van Hees (The Netherlands ) et al. Systematic review of image-based artificial intelligence algorithms for molecular diagnostics in prostate cancer pathology |
| P24 |
Francesca Vanzo (Italy) et al. Leveraging AI in Digital Pathology: Supporting Pathologists in Telepathology-Driven Diagnostics Workflows |
| P26 |
Behnaz Elhaminia (United Kingdom) et al. Macrophage Scoring Algorithm with A Semi-Supervised Deep Learning Framework for Efficient Segmentation with Limited Labelled Data |
| P27 |
Max Jackson (United Kingdom) et al. Applying deep learning models to cytospin images from intraocular biopsies of Choroidal Melanoma and Metastatic carcinomas to the choroid. |
| P28 |
Mohamed M Abdrabbou (Germany) et al. Understanding Immunotherapy Resistance Mechanisms in Urothelial Carcinoma Immune Microenvironment Phenotypes |
| P29 |
Sabina Köfler (Austria) et al. Computer-aided diagnostics helps to accurately determine different expression levels of claudin-18.2 in gastric cancer |
| P30 |
Fatemeh Zabihollahy (Canada) et al. Artificial Intelligence for Autonomous Detection of Lymph Node Metastasis in Prostate Cancer |
| P31 |
Phoenix Wilkie (Canada) et al. Scoring the unseen: A smarter way to evaluate clustering in digital pathology |
| P32 |
Chung-Yueh Lien (Taiwan) et al. Leveraging FHIR and DICOM for Interoperable Digital Pathology and Reporting in Nonalcoholic Steatohepatitis |
| P33 |
Yu Deok Choi (Republic of Korea) et al. Ensemble Deep Learning Model to Predict Lymphovascular Invasion in Gastric Cancer |
| P34 |
Nadine S. Schaadt (Germany) et al. Software and seminar format to jointly teach computational pathology in biomedical and computational academic curricula |
| P35 |
Jan Weber (Germany) et al. Feature extraction from spatial cell composition in ulcerative colitis immune microenvironment |
| P36 |
Tuo Yin (Belgium) et al. Deep Learning-Based End-to-End H-Score Quantification Framework for Whole Slide Images in Breast Cancer |
| P37 |
Maria Giulia Carta (Germany) et al. An integrative pathology workflow to enhance molecular diagnostics in precision oncology |
| P38 |
Celia Benitez Camacho (United Kingdom) et al. Deep Learning-Based Prediction of Ki-67 Expression in H&E-Stained Images |
| P39 |
Aray Karjauv (Germany) et al. Explainable AI for Foundation Models in Digital Pathology |
| P40 |
Nihad BENDADA SOONEKINDT (France) et al. IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE FOR THE DIAGNOSIS OF INTRAHEPATIC DUCTULAR LESIONS |
| P41 |
Ali Mammadov (France) et al. Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology |
| P42 |
Narinder Janghra (England) et al. Algorithm pathologist correlation: Quantitative comparison of immunohistochemical staining for claudin 6 in ovarian carcinoma TMA |
| P43 |
Judit Moreno-Crespi (Spain) et al. First Steps in Digital Pathology for Higher Non-University Students |
| P44 |
Mark Schuiveling (the Netherlands) et al. A comparison of AI-detected tumor-infiltrating lymphocytes and foundation models for immune checkpoint inhibitor response prediction in melanoma |
| P45 |
Aymen Sadraoui (Gif-Sur-Yvette) et al. Support vector machine model including computational pathology to predict early recurrence of hepatocellular carcinoma after surgical resection |
| P46 |
Pil-Jong Kim (South Korea) Pathology Foundation Models to Reveal Prognostic Features and Molecular Correlations in Head and Neck Squamous Cell Carcinoma |
| P47 |
Rémy Peyret (France) et al. Annotation Discrepancies in Prostate Cancer Gleason Grading: Implications for Deep Learning Training |
| P48 |
Sarah Volinsky-Fremond (The Netherlands) et al. Comparing Foundation Models Across Key Diagnostic and Prognostic Tasks: Endometrial Cancer as a Use Case |
| P49 |
Laura Schwarzmann (Germany) et al. AI-based molecular classification of a real-world endometrial cancer cohort on H&E whole-slide-images for prognostic stratification |
| P50 |
María Jesús García-González (Spain) et al. The Role of Sample Quality and Digitization in AI-Driven Digital Pathology |
| P51 |
Anastasiia Denysenko (Ukraine) et al. "Nuclear Diagnostics": Intelligent System for Personalized Diagnosis of Breast Oncology |
| P52 |
Gonçalo Borrecho (Portugal) et al. PathProfiler as a Quantitative Quality Control Software for Prostate Biopsies – Pilot Study in Centro de Anatomia Patológica Germano de Sousa |
| P53 |
Ivet Alexandra Herrero Aguilar (Spain) et al. Satisfaction of Pathologists with the Implementation of Digital Pathology in a Secondary-Level Hospital: A Cross-Sectional Survey Study |
| P54 |
Laura Sáez (Spain) et al. Closing the Loop: Continuous AI Model Improvement Through Pathologist-Guided Feedback |
| P55 |
Suha Berk Kukuk (New York,USA) et al. Automated Invasive Area Detection Algorithm for Breast Cancer |
| P56 |
Amjad Khan (Switzerland) et al. Leveraging foundation models to improve lymph node segmentation in colorectal cancer whole slide images |
| P57 |
Pedro Montero-Pavón (Spain) et al. Artificial Intelligence-Based Prediction of Molecular Subtypes in Breast Cancer Using Hematoxylin and Eosin-Stained Whole Slide Images |
| P58 |
Ichiro Mori (Japan) et al. Development and features of Digital Pathology Diagnostic System among our group hospitals including Vietnam |
| P59 |
Antonietta Salerno (Australia) et al. Integrating spatial multi-omics to investigate metal-driven tumour evolution in gliomas |
| P60 |
Harshwardhan M Thaker (United States) et al. Adoption and Impact of Digital Pathology and AI at a Mid-Sized Pathology Department: Experience from the University of Texas Medical Branch (UTMB) |
| P61 |
Sercan Cayir (New York, USA) et al. Comparative Analysis of State-of-the-Art Extractive Question Answering Models for Histopathology Report Information Extraction |
| P62 |
Misgina Tsighe Hagos (Sweden) et al. Validating Conformal Prediction for Cervical Atypia Classification |
| P63 |
Sergio Vazquez Montes de Oca (Switzerland) et al. A Synthetic Data Framework for Benchmarking Single-Cell Computational Methods in Image-Based Spatial Transcriptomics |
| P64 |
Walid Sabhi (Spain) et al. Automated Cell Segmentation for Oligodendroglioma |
| P65 |
Yijie Zhu (United Kingdom) et al. Lung Cancer Segmentation on Macro Images with Deep Learning |
| P66 |
Jan-Niklas Runge (Switzerland) et al. Real-world performance of AI-based tumor cell content quantification |
| P67 |
Manav Shah (United States) et al. The Impact of Tissue Section Thickness on Image Quality and Computational Feature Extraction in Digital Pathology |
| P68 |
Caner Ercan (Houston, TX, USA) et al. Path-omics: Computational pathology approach to predict Barrett’s esophagus progression using aneuploidy and ecological microenviromental metrics |
| P70 |
Osama Khan (United States) et al. A Multicenter Validation of a Novel Digital Pathology Molecular Workflow for Minimal Residual Disease Testing of Oncologic Specimens |
| P71 |
Nainesh Joshi (India) et al. Optimizing Telepathology Workflows: A Data-Driven Approach to Digital Case Submission and Quality Assessment |
| P72 |
Christian Harder (Germany ) et al. Patch Engineering: Novel Data Augmentation for Multi-Tissue Transitional Region Segmentation with Sparse Annotations |
| P74 |
Nilay Bakoglu Malinowski (Turkey) et al. Optimizing a Scanning Protocol for Liquid-Based Cervical Cytology on Whole Slide Images Using Z-Stack |
| P75 |
Costanza Gori (Italy) et al. Multicolor, fast volumetric imaging of cancer samples with multi-confocal light-sheet microscopy |
| P76 |
Angela Crispino (Italy) et al. H&E-Based TIL Assessment in OSCC: A Novel AI Approach Bypassing Immunohistochemistry |
| P73 |
Philipp Seegerer (Germany) et al. Explainable AI for Weakly Supervised Membrane Expression Scoring |
| P77 |
Angela Crispino (Italy) et al. Deep Learning Reveals Stromal Signatures of Prognosis in Oral Squamous Cell Carcinoma |
| P78 |
Mina Jamshidi Idaji (Germany) et al. Beyond Attention Heatmaps: Better Explanations for Multiple Instance Learning Models in Histopathology |
| P79 |
Anna Salut Esteve Domínguez (The Netherlands) et al. AI-powered Classification of Thymic Epithelial Tumors Using Histopathological Analysis of H&E Whole Slide Images |
| P80 |
Shrief Abdelazeez (Warsaw, Poland) et al. Color Standardization in Digital Pathology: A Comparative Study of Stain Normalization Methods for H&E Whole Slide Images |
| P81 |
Violeta Liuba Calin (Romania) et al. INTELLIGENT PROCEDURE BASED ON DIGITAL HOLOGRAPHIC IMAGING FOR COLONIC POLYPS AND ADENOCARCINOMAS GRADING |
| P82 |
Francisco José Carrasco Tena (Spain) Enhancing Digital Pathology Interoperability with Meditecs DICOMPath: Insights from the DICOM WG-26 2025 Connectathon |
| P83 |
Felix Anne Dikland (The Netherlands) et al. A scoping review of automated tumor-stroma ratio assessment in colorectal cancer: Current approaches and challenges |
| P84 |
Matteo Montalbano (Italy) et al. Quantitative image analysis of CD4 and CD8 in colon medullary carcinoma |
| P85 |
Richard Salmon (United Kingdom) et al. Aging of AI Caused by Scanner Drift Can Be Rescued by Color Calibration |
| P86 |
Christian Grashei (Germany) et al. Using Large Language Models for Extracting Slide-level Information from Pathological Reports |
| P87 |
José F Carreño Martinez (Switzerland) et al. Biological information derived from clinical samples is hindered by upstream processing steps in Image-based Spatial Transcriptomics data |
| P88 |
Kai Rakovic (United Kingdom) et al. Self-supervised learning identifies cellular neighbourhoods from multiplex immunofluroescence images |
| P89 |
Qi Zhang (Canada) et al. A Deep Active Learning Framework for Mitotic Figure Detection with Minimal Manual Annotation and Labelling |
| P90 |
Zaka-Ud-Din Muhammad (Italy) et al. FL-Net: Fast and lightweight Network for Breast Cancer Segmentation |
| P91 |
Oscar Pina (Spain) et al. Unsupervised Domain Adaptation for Cell Detection Across Histopathological Stains |
| P92 |
Susanne E Pors (Denmark) et al. Automated AI-assisted Ashcroft scoring of lung fibrosis in a bleomycin-induced and spirometry-confirmed mouse model of IPF |
| P93 |
İrem Özöver Çelik (Turkey) et al. Transitioning to a Paperless Pathology Workflow |
| P94 |
Rina Mehmeti (Switzerland) et al. AI-Based Detection and Quantification of Fibrosis in Kidney Biopsies Stained with Masson's Trichrome |
| P95 |
Bruno Coelho (Portugal) et al. Enhancing Forensic Pathology: AI and Computational Histopathology in Coronary Autopsy Analysis |
| P96 |
Anna Välimäki (Finland) et al. Large language models outperform human experts in pathology multiple choice questions |
| P97 |
Iancu Emil Plesea (Romania) et al. Morphometric assessment of cardiac interstitial mature collagen network depending on age |
| P98 |
Jingsong Liu (Germany) et al. HASD: Hierarchical Adaption for pathology Slide-level Domain-shift |
| P99 |
Maryam Mohammadlou (Finland) et al. Impact of TLR9 Expression and Tumor Microenvironment on Survival Outcomes in Glioma Patients: A Histological and Molecular Analysis |
| P100 |
Iancu Emil Plesea (Romania) et al. Quantitative assessment of interstitial mature collagen network depending on cause of death |
| P101 |
Kajsa Ledesma Eriksson (Sweden) et al. Graph Neural Networks for Spatially-Aware Phenotyping of Breast Cancer Whole Slide Images |
| P102 |
Andrea Camilloni (Sweden) et al. End-to-end Deep Learning Model for Predicting Recurrence-Free Survival after Radical Prostatectomy |
| P103 |
Jacqueline E. van Hees (The Netherlands ) et al. Deep multiple instance learning for predicting BRCA gene mutations from digitized prostate cancer pathology slides |
| P104 |
Mette Bak Brogård (Denmark) et al. Digital quantification of Ki67 and PRAME in challenging melanocytic lesions: A novel diagnostic tool |
| P105 |
José Teixeira (Portugal) et al. H&E to IHC virtual staining in breast cancer: methods, benchmarking, and challenges |
| P106 |
Raghubansh Gupta (USA) et al. Volumetric scanning enhances the mitosis algorithm performance by using shape and texture analysis across Z stacks similar to fine focus of microscopy |
| P107 |
Anilpreet Singh (India) et al. Deep Learning in Bone Marrow Diagnostics: The BaMBo & BoMBR Datasets for Segmentation and Reticulin Quantification |
| P108 |
Patricia Switten Nielsen (Denmark) et al. Mapping the immune-cell landscape for optimal index calculation using AI-powered image analysis of multiplexed immunohistochemistry in breast cancer |
| P109 |
Akira I. Hida (Japan) et al. Deep Learning-Based, Fully Automated Analysis of histological biomarkers of ER, PgR, HER2 and Ki-67 on Invasive Breast Carcinoma |
| P110 |
Rushabh Mehta (South Korea) et al. Evaluating a Web-Based AI Algorithm for Pap Smear Pre-Screening: A Multicenter Pilot Study in Korea and India |
| P111 |
Volodymyr Chapman (United Kingdom) et al. Automated IHC distinguishes risk groups in DLBCL |
| P112 |
Pascal Klöckner (The Netherlands) et al. Diffusion-based H&E-to-HER2 virtual staining: the impact of data alignment |
| P113 |
Hrafn Weishaupt (Norway) et al. Combining unsupervised and active learning in training a classifier for global glomerulosclerosis detection |
| P114 |
Viola Iwuajoku (Germany) et al. An Equivalency Study of Digital Pathology for Clinical Routine Diagnostics |
| P115 |
Benedetta Manzato (the Netherlands) et al. Alignment of consecutive multi-modal whole-tissue slides using image features |
| P116 |
Nazanin Mola (Norway) et al. Enhancing Quantification of Interstitial Fibrosis in Non-Neoplastic Kidney Disease through Structural Segmentation |
| P117 |
Naoko Tsuyama (Japan) et al. Next-generation image compression for digital pathology: JPEG XL optimises storage, speed, and clinical workflow efficiency |
| P118 |
Jari Claes (Belgium) et al. Modelling of spatial association and disease stage within the coregistered fluorescent stained tumor microenvironment data in mice |
| P119 |
Adriana Katherine Calapaquí Terán (Spain ) et al. Lobular breast cancer: A challenging subtype for artificial intelligence (AI) pathology tools |
| P120 |
Borghild Larsen (Norway) et al. Evaluating iterative deep learning as a labeling-efficient strategy for tubular segmentation in digital nephropathology |
| P121 |
Jiří Horák (Czechia) et al. Inter-rater Disagreement In Digital Pathology |
| P122 |
Elissa Woo (Canada) et al. A novel approach to the assessment of mismatch repair protein immunohistochemistry utilizing digital cytometric analysis |
| P123 |
Tom Bisson (Virchowweg 15, 10117 Berlin, Germany) et al. Let’s UNITE in Transatlantic Health Data Use: Introducing the “Understanding through Networked International Transatlantic Exploration” Project |
| P124 |
Clément Grisi (the Radboud university medical center) et al. AI-Driven Cancer-Agnostic Histological Features to Improve TP53 Mutation Prediction in Prostate Cancer |
| P125 |
Eduard Dorca Duch (Spain) et al. Multimodal AI for Atypical Hyperplasia Diagnosis: A Comparative Study of CNNs, GNNs, and Hybrid Models |
| P126 |
Adam Kukučka (Czechia) et al. AI model for Ki-67 index prediction for breast cancer trained purely on existing diagnostic data |
| P127 |
Özben Yalçın (Türkiye) et al. Evaluation of Digital Pathology Imaging in Punch Biopsy: Quality, Processing Time, Workflow, and Diagnostic Usability |
| P128 |
Aniek Eijpe (Netherlands) et al. Disentangling Shared and Specific Information between Whole-Slide Images and Gene Expression for Interpretable Multimodal Cancer Survival Prediction |
| P129 |
Yosef Molchanov (Israel) et al. Overdiagnosis in Digital Pathology: The Potential Role of Artificial Intelligence and the Global Challenge of Diagnostic Gaps |
| P130 |
Dirk Valkenborg (Belgium) et al. Gradient boosting to predict individual cell types from nuclei segmentations |
| P131 |
Johannes Lotz (Germany) et al. Accelerating Routine Pathology Workflow with Digital Image Registration |
| P132 |
Reinhold Wimberger-Friedl (The Netherlands) et al. An AI-enabled and Automated Workflow for Tissue Macrodissection in Molecular Pathology |
| P133 |
Mariana Carvalho (Portugal) et al. Automated Segmentation of Unstained Kidney Biopsies: The Feasibility and Challenges |
| P134 |
Subhash Yadav (Mumbai, India) et al. Colorectal Adenocarcinoma Segmentation Model – Validation of a Deep Learning Model on In-House Colorectal Biopsies |
| P135 |
Joar von Bahr (Finland ) et al. Prospective validation of image-based artificial intelligence for cervical cancer screening in a resource-limited setting |
| P136 |
Namratha S (India) et al. Validation of a AI driven sTIL quantification pipeline against pathologist assessments in Head Neck Squamous Cell Carcinoma |
| P137 |
Swann Ruyter (France) et al. Diffusion Models for Morphology-Guided Transcriptomics: A Computational Framework |
| P138 |
Tripti Bameta (India) et al. Evaluation of Histopathology Foundation Models for General Purpose Task on head and Neck Cancer Tissue |
| P139 |
Nilay Bakoglu Malinowski (Turkey) et al. Optimizing a Scanning Protocol for Liquid-Based Cervical Cytology on Whole Slide Images Using Z-Stack |
| P140 |
Anshuman Sharma (India) et al. Survival Modelling using whole slide images in Head Neck Squamous cell carcinoma achieves good predictive value |
| P141 |
Mikhail Karasikov (Switzerland) et al. Efficient training of state-of-the-art pathology foundation models on orders of magnitude fewer WSIs |
| P142 |
Lucas Farndale (Scotland) et al. Super Vision Without Supervision: Multimodal Knowledge Distillation for Enhanced Representation Learning from Biomedical Imaging |
| P143 |
Maximilian C. Koeller (Austria) et al. Metadata Quality Assurance Using Deep Learning Based Automated Stain Detection |
| P144 |
Christian Matek (DE) et al. Predicting molecular subtypes of muscle-invasive urothelial carcinoma using Histopathology Foundation Models |
| P145 |
Kim Nijsten (Belgium) et al. Mapping the tumor microenvironment combining cyclic multiplex immunofluorescence with standard Hematoxylin-Eosin staining for whole slide imaging |
| P146 |
Calum MacAulay (Canada) et al. One Pixel to Many Objects Mapping for Nuclear Segmentation and Marker Evaluation in Spatial Biology |