Through a comprehensive evaluation of model complexity and number of parameters, it was determined that the overall performance of the proposed model is the best when eight group convolutions are used ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, making it more applicable in clinical settings. The algorithm outperformed ...

Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...