Medical Information Computing : First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Student Board Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Revised Selected Papers / / edited by Udunna Anazodo, Naren Akash, Moritz Fuchs, Celia Cintas, Alessandro Crimi, Tinahse Mutsvangwa, Farouk Dako, Willam Ogallo

• Autore: Anazodo Udunna
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (452 pages)
• Disciplina: 006
• Soggetto topico: Image processing - Digital techniques; Computer vision; Biomedical engineering; Computer Imaging, Vision, Pattern Recognition and Graphics; Medical and Health Technologies
• Altri autori: AkashNaren FuchsMoritz CintasCelia CrimiAlessandro MutsvangwaTinahse DakoFarouk OgalloWillam
• Nota di contenuto: First MICCAI Meets Africa Workshop, MImA 2024 -- EARLY DETECTION OF LIVER FIBROSIS -- Optimized Brain Tumor Segmentation for resource constrained settings: VGG-Infused U-Net Approach -- Optimizing Classification of Congestive Heart Failure Using Feature Weight Importance Correlation -- MCL: Multi-Level Consistency Learning for Medical Image Segmentation -- Trustworthiness for Deep Learning Based Breast Cancer Detection Using Point-of-Care Ultrasound Imaging in Low-Resource Settings -- Advancing the Reliability of Ultra-Low Field MRI Brain Volume Analysis using CycleGAN -- Deep Learning based Non-Invasive Meningitis Screening using High-Resolution Ultrasound in Neonates and Infants from Mozambique, Spain and Morocco -- Automated Segmentation of Ischemic Stroke Lesions in Non-Contrast Computed Tomography Images for Enhanced Early Treatment and Prognosis -- Spatial Attention-Enhanced Diffusion Model for Multiple Sclerosis MRI Synthesis -- An Automated Pipeline for the Identification of Liver Tissue in Ultrasound Video -- Democratizing AI in Africa: Federated Learning for Low-Resource Edge Devices -- Generative Style Transfer for MR Image Segmentation: A case of Glioma Segmentation in Sub-Saharan Africa -- Impact of Skin Tone Diversity on Out-of-Distribution Detection Methods in Dermatology -- Deployment and Evaluation of Intelligent DICOM Viewers in Low-Resource Settings: Orthanc Plugin for Semi-Automated Interpretation of Medical Images -- Enhancing Soil-transmitted Helminths Diagnosis through AI: A Self-Supervised Learning Approach with Smartphone-Based Digital Microscopy -- Capturing Complexity of the Foot Arch Bones: Evaluation of a Statistical Modelling Framework for Learning Shape, Pose and Intensity Features in a Continuous Domain -- Explainability-Guided Deep Learning Models For COVID-19 Detection Using Chest X-ray Images -- Feasibility of Open-Source Tracking-Based Metrics in Evaluating Ultrasound-Guided Needle Placement Skills in Senegal -- Automatic Segmentation of Medical Images for Ischemic Stroke in CT Scans for the Identification of Sulcal Effacement -- AfriBiobank: Empowering Africa’s Medical Imaging Research and Practice Through Data Sharing and Governance -- Benchmarking Noise2Void: Superior Denoising of Medical Microscopic Images -- First MICCAI Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024 -- Self-consistent deep approximation of retinal traits for robust and highly effcient vascular phenotyping of retinal colour fundus images.-Non-Parametric Neighborhood Test-Time Generalization: Application to Medical Image Classification -- Client Security Alone Fails in Federated Learning: 2D and 3D Attack Insights.-Context-Guided Medical Visual Question Answering -- GRAM: Graph Regularizable Assessment Metric -- Unsupervised Analysis of Alzheimer’s Disease Signatures using 3D Deformable Autoencoders -- Deep Feature Fusion Framework for Alzheimer’s Disease Staging using Neuroimaging Modalities -- Explainable Few-Shot Learning for Multiple Sclerosis Detection in Low-Data Regime.
• Sommario/riassunto: This book presents a series of revised papers selected from the First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, which was held in Marrakesh, Morocco, during October 6, 2024. MImA 2024 accepted 21 full papers from 45 submissions; for EMERGE 8 papers are included from 9 submissions. They describe cutting-edge research from computational scientists and clinical researchers working on a variety of medical image computing challenges relevant to the African and broader global contexts, as well as emerging techniques for image computing methods tailored to low-resource settings.
• Titolo autorizzato: Medical Information Computing
• ISBN: 9783031791031; 3031791037
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910983298103321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 2240