SenTumorNet: A Lightweight 3D U-Net Model for Brain Tumor Segmentation in Sub-Saharan African MRI Data

Lightweight Brain Tumor Segmentation on Low-Resource Systems: A Step-by-Step Guide with 3D U-Net v1

The application of deep learning methods in the healthcare has gained significant popularity and rel

Lightweight Brain Tumor Segmentation on Low-Resource Systems: A Step-by-Step Guide with 3D U-Net v2

The application of deep learning methods in the healthcare has gained significant popularity and rel

Optimizing the nnU-Net model for brain tumor (Glioma) segmentation Using a BraTS Sub-Saharan Africa (SSA) dataset

Medical image segmentation is a critical achievement in modern medical science, developed over decad

A Fast, Lightweight nnUNet-Based Brain Tumor Segmentation Model Optimized for Low-Resource African Settings

BrainAdaptNet: A few-shot learning model for brain tumor segmentation in low-quality MRI

Segmentation of brain tumors in low-quality magnetic resonance imaging (MRI) remains a challenge, es

Brain Tumour Segmentation for Sub-Saharan African Population Using 3D UNet

Brain Tumour Segmentation for Sub-Saharan African Population Using 3D UNet

Poster presented at the Deep Learning Indaba 2023 by Abdulquddus Ajibade