Del i serien Communications in Computer and Information Science

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

Häftad, Engelska, 2025

AvUdunna Anazodo,Naren Akash,Moritz Fuchs,Celia Cintas,Alessandro Crimi,Tinahse Mutsvangwa,Farouk Dako,Willam Ogallo

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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.

Produktinformation

Utgivningsdatum2025-02-09
Mått155 x 235 x 18 mm
Vikt487 g
FormatHäftad
SpråkEngelska
SerieCommunications in Computer and Information Science
Antal sidor301
FörlagSpringer International Publishing AG
ISBN9783031791024

Tillhör följande kategorier

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.

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