Technological innovation is rapidly transforming neuro-oncologic surgery, yet a major unmet need remains: translating promising tools into reliable, ...

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 ...

Researchers from the University of Tartu Institute of Physics have developed a novel method for enhancing the quality of three-dimensional images by increasing the depth of focus in holograms fivefold ...

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 ...