Abstract: Large-scale, big-variant, high-quality data are crucial for developing robust and successful deep-learning models for medical applications since they potentially enable better generalization ...
Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
This repository provides an end-to-end pipeline for medical image segmentation using deep learning. Implemented in Python with TensorFlow, OpenCV, and other popular libraries, this project includes ...
This project implements a 2D pore-throat network extraction algorithm for porous media images. It uses a modified watershed segmentation approach based on Distance Transform and H-maxima markers to ...
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