MICCAI Meets Africa Workshop

Congratulations to authors on their accepted papers.

Workshop Proceedings

Accepted papers presented at the workshop will be published in camera-ready format after the workshop in Springer Nature's Communications in Computer and Information Science (CCIS).

Camera-ready Submission Instruction

Authors are required to submit their camera-ready papers addressing reviewer feedback in their papers along with rebuttal letter, electronically via the submission portal. Camera-ready papers must adhere strictly to the Springer CCIS style guidelines. Authors should consult Springer’s Instructions for Authors of Proceedings and use either the LaTeX and MS Word templates available on the Communications in Computer and Information Science author's page for preparation of their camera-ready paper. Modifications to the template are not allowed, and failure to comply with these formatting guidelines will result in the paper's rejection. Authors should review the Springer's instructions for authors of papers to be submitted to Springer and the publisher's Code of Conduct for Book Authors.

Authors interested in Open Choice publication can refer to CCIS webpage for prices and additional information.

Submission Portal

Submission Portal: https://cmt3.research.microsoft.com/MICCAImeetsAFRICA2024/

Congratulations to authors on their accepted papers.

Impact of Skin Tone Diversity on Out-of-Distribution Detection Methods in Dermatology

Trustworthiness for Deep Learning Based Breast Cancer Detection Using Point-of-Care Ultrasound Imaging in Low-Resource Settings

Feasibility of Open-Source Tracking-Based Metrics in Evaluating Ultrasound-Guided Needle Placement Skills in Senegal

Spatial Attention-Enhanced Diffusion Model for Multiple Sclerosis MRI Synthesis

Capturing Complexity of Foot Arch Bones: Evaluation of a Statistical Modelling Framework for Learning Shape, Pose & Intensity Features in a Continuous Domain

Automated Segmentation of Ischemic Stroke Lesions in Non-Contrast Computed Tomography Images for Enhanced Early Treatment and Prognosis

An Automated Pipeline for the Identification of Liver Tissue in Ultrasound Video

Enhancing Soil-transmitted helminths Diagnosis through AI: A Self-Supervised Learning Approach with Smartphone-Based Digital Microscopy

Optimized Brain Tumor Segmentation for resource constrained settings: VGG-Infused U-Net Approach

Early Detection of Liver Fibrosis

Optimizing Classification of Congestive Heart Failure Using Feature Weight Importance Correlation

MCL: Multi-Level Consistency Learning for Medical Image Segmentation

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

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

Deployment and Evaluation of Intelligent DICOM Viewers in Low-Resource Settings: Orthanc Plugin for Semi-Automated Interpretation of Medical Images

Explainability-Guided Deep Learning Models For COVID-19 Detection Using Chest X-ray Images

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

Workshop Proceedings