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Is Radiomics Moving in the Right Direction? - A Structured Validation of Published Radiomics Models for Rectal CancerLukas Dünger
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Development of a Deep Learning-Based prototype for the Automatic Analysis of Dynamic Digital Radiography (DDR) in Chronic Cervical Pain.Matilde Pavan
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STRUCTURED TRANSFORMATION OF UNSTRUCTURED PROSTATE MRI REPORTS USING LARGE LANGUAGE MODELS (LLMS)Luca Di Palma
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LLM-Assisted Analysis of Incidental Findings in Whole-Body MRI: A Multicenter Preventive Screening StudyMarco Alì
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Comparing Radiologists and AI in the Detection of Breast Lesions on 2D MammographyJeanne Ventre
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Evaluation of Vendor-Agnostic Deep-Learning Denoising in Pediatric Low-Dose Non-Contrasted Cranial CTSebastian Steinmetz
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The Role and Challenges of AI Training in Radiology: Insights from a CT Brain AI Implementation SurveyDr Geraldine Dean
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User’s preferences to build up criteria for effective implementation of eXplainable AI denoising in PET/CT Mélanie Champendal
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AI-Based Prostate Lesion Segmentation on In-House mp-MRI: Impact of U-Net Variants and PI-RADS LevelsSaman Fouladi
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Comparative evaluation of proprietary and open-source large language models for systematic multi-source information extraction in interventional oncologyElif Can
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Maximizing Efficiency in Lower Limb and Foot Radiography Using AI-Driven Tools for Measurement and ReportingNor-eddine Regnard
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Applying Artificial Intelligence to the Detection of Secondary Bone Lesions on CTNor-eddine Regnard
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From development to implementation: a systematic review on the current maturity status of artificial intelligence models for patients with colorectal cancer liver metastasesRuby Kemna-presented by Marius Strampel
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Radiomic Strategies for Chemotherapy-Associated Steatohepatitis in Colorectal Liver Metastases: Virtual Biopsy or Whole-Liver Analysis? Angela Ammirabile
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Advancing AI integration within radiology through multidisciplinary collaboration: the impact of an AI Study Conference Avneet Gill
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Think Aloud Study for Knowledge (TASK) about AI user interface perceptionsAvneet Gill
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Evaluating Large Language Model-Generated Brain MRI Protocols: Performance of GPT4o, o3-mini, DeepSeek-R1 and Qwen2.5-72BSu Hwan Kim
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AI education intervention for medical imaging professionals: development, delivery and outcomesGeraldine Doherty
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Enhanced Neurovascular Imaging with Ultra-High-Resolution CT and Deep Learning-Based Image Reconstruction: Focus on Intracranial Veins and SinusesSebastian Steinmetz
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Generative Adversarial Networks for MRI images normalization: a multicentric study on gliomas characterization via Radiomics analysisAlessia Lindemann
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Feasibility of small Large Language Models for retrospective structuring of free-text radiology reports into RECIST formatNicolas Rehbach
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Teaching Radiomics through an Interactive Platform: A Qualitative Study on the Use of QuantImage in Medical EducationMélanie Champendal
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Progress in Radiological Diagnosis of Hepatocellular Carcinoma: Integration of Conventional Criteria and Radiomic Features in Indeterminate Liver LesionsAgostino Inzerillo
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From Pixels to Prognosis: A Head-to-Head Comparison of Custom 3D and 2D nnU-Net Models for Pulmonary Embolism Detection and Risk StratificationEzio Lanza
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Anti PD-1 response prediction with radiomics. The challenges of reproducibility and the struggle towards clinical practiceEmanuele Barabino
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Artificial Intelligence in Diagnosing Bone Trauma on Radiographs: Do Foreign or Medical Devices Affect Diagnostic Performance?Roberto Cannella
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Perceptual versus quantitative similarity in AI-denoised low-dose PET/CT ImagingMélanie Champendal
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Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflowRuby Kemna
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Validation of TotalSegmentator models for whole-body CT and MR organs segmentation. A comparative study.Georgios Lappas
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mdknee: AI-based MRI assessment of knee cartilage damageTiziano DAlbis
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Bridging the Data Gap: Deep Learning Lymph Node Segmentation in Pediatric OncologyAndreas Bucher
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Beyond Nodules: A Deep Learning Approach for Comprehensive Lung Tumour Segmentation on CTLiliana Petrychenko
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GPU-Accelerated ML Pipeline for Medical Imaging: Bridging Research and Clinical DeploymentEric Frodl
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Mapping the European market of CE-Certified AI for radiotherapy: A 2025 inventory towards transparency and responsible adoptionMarlie J.H. Besouw
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The Effect of Explanations from Large Language Models on Diagnostic Accuracy in Radiology: A Randomized Controlled TrialBoj Friedrich Hoppe
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Development of interpretable imaging biomarkers for survival prediction and neoadjuvant therapy response assessment in pancreatic ductal adenocarcinomaAmber Lamoré
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Automated Lymph Node Segmentation in Chronic Lymphocytic Leukemia Patients using Fine-tuned nnU-NetMaleyka Seyidova
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Training radiologists for the European Health Data SpaceAlessandro Catanese
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Automated peripheral nerve segmentation for MR-neurographyNedim Beste
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MRI‑based scoring system to predict spondylodiscitis: the SPONDY-ScoreCaterina Beatrice Monti
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Addressing Automation Bias in when using AI tools in Radiology: Lessons from AI-Assisted Lung Nodule EvaluationDr Geraldine Dean
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AI-assisted fracture detection in adult patients: impact on medical studentsDalila Cascio
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Automated coronary tree segmentation using a 3D U-Net based deep learning approachEra Stambollxhiu
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Knowledge and perceptions of chatbots and generative AI among allied health professions (AHP) middle managersNicola Iosca
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 Clinicians’ perceptions of Large Language Model (LLM) outputs for simplification of radiology reports of the appendicular skeleton. Clare Rainey
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Radiology AI for Prioritised Imaging and Diagnosis of Lung Cancer (RAPID-LC): the stakeholders perspective.Clare Rainey
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Data-driven energy efficiency in a high-throughput PET/CT department: a model for sustainable nuclear medicinemarco de summa
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Performance of AI Assistance in Detecting Thoracic Abnormalities on Chest Radiographs: A Comparative Study with Readers of Varying Experience Rosa Alba Pugliesi
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Artificial Intelligence in Spinal Imaging for Osteoporotic Vertebral Compression Fractures: A Systematic Review and Meta-AnalysisAlistair Paterson
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Intra-Procedural Radiomic Analysis of Ablated Liver Tumors: Unveiling Hidden Information Through Delta FeaturesEmanuele Barabino
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Structured versus free-text reports: Analysis of the reading efficiency using eye tracking Lukas Müller
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How Compressed Sense acceleration impacts the Central Nervous System Magnetic Resonance Imaging energy consumptionSelmina Kalari
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Automated Extraction of TNM Staging from Head and Neck Squamous Cell Carcinoma Imaging Reports Using ChatGPT-4.0Caterina Giannitto
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Artificial Intelligence for the Detection of Typically and Non-Typically Benign Nodules on Chest CT Souhail Bennani
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AIDA: A Comparative Study Between Clinicians and Large Language Models in Emergency Computed TomographyCaterina Giannitto
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Automatic Segmentation of Hepatocellular Carcinoma (HCC) Using Deep Learning on Multi-Phase CT ScansMaria Macheda
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Automated CT-based Segmentation and Quantitative Volumetric Analysis of Pleural and Pericardial Effusions Miriam Kumpf
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Deploying PACS in LMIC Countries: Cost-Effective and Sustainable Strategies Enabling AI deploymentHERMAN OOSTERWIJK
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Integrating AI-Based Body Composition Metrics into Structured Radiology Reports: A Clinical Workflow SolutionTobias Jorg
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AI-powered chatbot and centralized knowledge base to support patients in Nuclear Medicine: project structure and operational outlookmarco de summa
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Self-Explainable AI and Attention for Interpretable Cancer Analysis with Image and Omics Data (Multi-Modal): A Systematic Review
Muruganantham Jaisankar
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Anatomy Weighted Feature Diffusion in Graph Neural Networks for Robust Lesion TrackingMarius Strampel
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Advanced Imaging, AI and Device Innovation in Interventional radiologyIrene Nieri
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From Uncertainty to Insight: A Hybrid Machine Learning Tool for Interpreting B3 Breast Lesions in Breast MRIEva Panourgias
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Design and Initial Evaluation of an Ontology for Artificial Intelligence Model and Dataset MetadataCharles Kahn
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Integrating phantom radiomic stability testing for reproducible ultrasound classification of sarcopenia in rectus femorisRicardo Teresa Ribeiro
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Greening with AI-MRI: Smart, Short, and SustainableFrancesco Mariotti
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The Role of AI in transforming breast cancer screening Eva Panourgias
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New Standards And You: Making Sense of the Evolving Landscape in Medical Imaging InformaticsMohannad Hussain
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Benchmarking AutoML Frameworks for Radiomics: A Comparative Evaluation of Performance, Efficiency and UsabilityJose Lozano
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Harmonizing Radiology Workflow and Education through Large Language Models: A Multi-Pronged Implementation StudyTessa Cook
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Building Bridges for AI Implementation in Clinical Practice: The Role of Community in Radiology and BeyondWillem Grootjans
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Artificial Intelligence in Videofluroscopy and Fibreoptic Endoscopic Evaluation of Swallowing Analysis: A Scoping reviewAlison Keys
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Joint Post-Market AI Act and MDR Requirements for Semiautonomous AI SaMD: A Radiology Case Study in Prostate CancerShakila Shojaei
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Opportunistic Artificial Intelligence CT-Calculations for Body Height and Body Mass Index to Improve Cachexia AssessmentTom Yang
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EVALUATING THE EFFECTIVENESS OF AI IN TRAUMA DETECTION: A THREE-YEAR MULTICENTER STUDY ACROSS 20 RADIOLOGY CENTERSSergey Morozov
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Assessment of radiology report quality and perception: a comparative study of human-written and LLM-generated lumbar spine MRI reportsMoreno Zanardo
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TEMPORAL DYNAMICS OF AI AND RADIOLOGIST INTERACTION: A MULTI-MODALITY, MULTI-CENTER ANALYSIS ACROSS 20 IMAGING CENTERSSergey Morozov
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"MRI Process Mapping for Non-communicative Patients: A Proposal AI Approach for Automated Safety Checklist Completion"CARLO VITALE
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Automating Deep Inferior Epigastric Artery Perforator (DIEAP) flap planning using Foundation ModelMatilde Andrade
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Harmonization strategies in multi-centric and multi-vendor prostate MRI and their impact on deep learning models’ generalization ability Grigorios Kalliatakis
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Robust Pleural Effusion Segmentation in Routine CT studiesAndreas Bucher
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DCE-MRI and Mammography integrated radiomic analysis in triple negative ductal invasive breast cancer patients. Comparison between BRCA and not BRCA mutated patients: Preliminary results.Cecilia Beretta
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