A deep learning-based medical imaging project for automatic brain tumor segmentation from multi-modal MRI scans using a 3D nnU-Net architecture with a Flask web interface.

Learn how backpropagation works using automatic differentiation in Python. Step-by-step implementation from scratch. #Backpropagation #Python #DeepLearning Man Watched Moose For Years—Then Gets ...

1 School of Science, Tianjin University of Technology and Education, Tianjin, China. 2 School of Big Data, Lvliang Vocational and Technical College, Lvliang, China. Early image segmentation was mainly ...

Abstract: Ultra-wide field (UWF) retinal imaging can improve the detection rate of retinal hemorrhage as compared with conventional fundus images. However, hemorrhages in UWF retinal images can also ...

Objective: Accurate anterior visual pathway (AVP) segmentation is vital for clinical applications, but manual delineation is time-consuming and resource-intensive. We aim to explore the feasibility of ...

If you’re looking for a low-mess, automatic way to dispense hand soap and you’d like to limit the viruses, germs, and bacteria you come into contact with daily, automatic soap dispensers are worth ...

When using auto I frequently get the following error during the computation (not at the start): Program received signal SIGSEGV: Segmentation fault - invalid memory ...

Abstract: Despite the impressive performance of current deep learning models in the field of medical imaging, transferring the lung segmentation task in X-ray images to clinical practice is still a ...