Medical Image Computing in Resource Constrained Settings

.- Are ECGs enough? Deep learning classification of pulmonary embolism using electrocardiograms.- Enhancing and Accelerating Vessel Annotations in Medical Imaging.- AST-n: A Fast Sampling Approach for Low-Dose CT Reconstruction using Diffusion Models.- Deep Ensemble Approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings.- Non-invasive mean Pulmonary Artery Pressure Prediction using Multi-Modal Feature Fusion of Chest X-ray and ECG.- Large Scale DICOM Compliance Evaluation of Medical Image Data Elements in Low-Resource Settings.- EDGE-KD: Explainability-Driven Guidance for Efficient Knowledge Distillation in Chest X-Ray Classification.- Contour-Guided Segmentation and X-ray Image Validation for Pneumonia Detection using Mobile Deep Learning in Low-Resource Settings.- From Development to Deployment of AI-assisted Telehealth and Screening for vision- and hearing-threatening diseases in resource-constrained settings: Field Observations, Challenges and Way Forward.- Brain Tumor Segmentation in Sub-Sahara Africa with Advanced Transformer and ConvNet Methods: Fine-Tuning, Data Mixing and Ensembling.- Multimodal Fusion for Melanoma Classification Using Dermoscopic Images and Clinical Metadata.- An Empirical Study on Liver Volumetry: Deep Learning-Based Estimation of Tumor and Remnant Liver Volumes for Preoperative Planning.- Towards Trustworthy Breast Ultrasound Segmentation using Monte Carlo Dropout and Deep Ensembles for Epistemic Uncertainty Estimation.- Lightweight 3D U-Net for Brain Tumor Segmentation on CPUs: Enabling Deep Learning in Low-Resource Environments.- Fetal Abdomen-Guided Ultrasound Reconstruction via Autoencoder For Optimal Frame Selection and Segmentation.- Recovering Diagnostic Value: Super-Resolution-Aided Echocardiographic Classification in Resource-Constrained Imaging.- SharpXR: Structure-Aware Denoising for Pediatric Chest X-Rays.- Uncertainty-Aware Evaluation of Deep Learning Object Detectors under Scarce and Evolving Test Datasets.- Advancing Fetal Ultrasound Image Quality Assessment in Low-Resource Settings.- LightDenoise-HL: A Compact Attention-Based Denoising Framework with Dual-Frequency Filtering for Endoscopic Imaging.- Accessible Skin Analysis: A Low-Cost Multispectral Imaging System with Skin-Mimicking Phantoms.- Development and Evaluation of an AI-Driven Telemedicine System for Prenatal Healthcare.- CoMViT: An Efficient Vision Backbone for Supervised Classification in Medical Imaging.- Designing AI Algorithms to Suit Local Context.- Global South Health Practitioners' Awareness and Perceptions of Integrating Artificial Intelligence in Radiological Workflows: A Quantitative Nationwide Study.- Attention-Enhanced Deep Learning for Multi-Class Alzheimer's Disease Classification Using Macular OCT Images in Low-Resource Settings.- Resource-Efficient Glioma Segmentation on Sub-Saharan MR.- TB Screening App: Smartphone Imaging of Tuberculin Skin Test Indurations for Latent Tuberculosis Screening in Low-Resource Settings.- Empowering Medical Equipment Sustainability in Low-Resource Settings: An AI-Powered Diagnostic and Support Platform for Biomedical Technicians.- SepsiGraph: A Graph-Based Multimodal Approach for Early Sepsis Prediction in Dynamic Resource-Constrained Clinical Settings.- Clinically-Informed Preprocessing Improves Stroke Segmentation in Low-Resource Settings.