Detection of DFUs in clinical settings and telemedicine platforms is another game-changer. YOLO (You Only Look Once), Faster ...

Well, they can. Models can be created that allow patients to self-segment in ways more accurate and relevant than ever before. The patient segmentation model discussed here divides the patient ...

A research team at Kumamoto University has developed a deep learning-based method for analyzing the cytoskeleton—the structural framework inside cells—more accurately and efficiently than ever before.

More information: Minxing Pang et al, CelloType: a unified model for segmentation and classification of tissue images, Nature Methods (2024). DOI: 10.1038/s41592-024-02513-1 Provided by Children's ...

Glaucoma diagnosis traditionally relies on a combination of fundus imaging, optical coherence tomography (OCT), intraocular ...

The model performed well across the 80 structures with a Dice score of 0.839 on an internal MRI test set. It also significantly outperformed two publicly available segmentation models (0.862 ...

U-NET, a convolutional neural network architecture, demonstrates exceptional performance in brain tumour segmentation, achieving 98.56% accuracy and 99% F-score in MRI image analysis. Brain health is ...