Background The reported prevalence and burden of coronary artery disease in young adults varies markedly in published studies ...

Celldetective is an open-source software integrating segmentation, tracking, and event detection to perform high-throughput end-to-end study of dynamic cell interactions, without requiring coding ...

Compare deep learning cell segmentation tools Cellpose and StarDist: how each works, how they differ by imaging type, and ...

Artificial intelligence (AI) in research histopathology is turning whole-slide images of preclinical tissue into structured, quantitative data rather than a pathologist's subjective impression alone.

A new deep-learning model improved surgeons’ recognition of pelvic anatomy in video-based PLND tests, though live surgical ...

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...

Abstract: Medical image segmentation plays a pivotal role in modern healthcare, enabling accurate disease diagnosis, treatment planning, and patient monitoring by precisely delineating anatomical ...

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 ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...