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.

No matter what type(s) of photography you like to pursue, mastering exposure is key to creating successful images. While it can be tempting to use your camera's screen to judge exposure, that display ...

For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...

Aiming at the problem of inaccurate fruit recognition and fruit diameter detection in the persimmon inspection process, this research proposes a novel persimmon accurate recognition and fruit diameter ...

ABSTRACT: Introduction: Pharmacies serve not only as medication dispensing points but also as key sites for patient education. Despite this, there is growing concern regarding patients’ comprehension ...

Abstract: This paper proposed an auto-adaptive threshold method of two-dimensional (2-D) histogram based on multi-resolution analysis (MRA), decreasing the calculation complexity of 2-D histogram ...

Instance segmentation has been the most challenging task in the field of computer vision, and its techniques are widely used in the fields of intelligent driving, intelligent medical imaging, remote ...

Python implementation of the adaptive seed (centroid) placement part in Adaptive-SNIC algorithm. Following figure shows the corresponding seeds produced by Adaptive-SNIC algorithm. It is clear that ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...