FireANTs, an open-source algorithm, combines AI optimization and geometry to quickly match complex medical images. The new method can accomplish what took weeks in minutes, detecting subtle changes that signal disease or cognitive decline, making it practical for clinical practice.
A team of scientists has found a naturally occurring Voronoi pattern in the Chinese money plant, which helps explain how plants create complex patterns on their leaves. This discovery sheds light on how plants solve problems in nature and may provide new insights into the math underlying evolution and development.
A new study in Nature Communications found that AI models exhibit a geometric property called convexity, which helps humans form and share concepts. Convexity is also linked to the performance of AI models on specific tasks.
A study discovers that traditional Chinese ice-ray lattice designs can provide unique stiffness and strength under asymmetric loads, offering an alternative to conventional gridshells. The research also explores the potential of integrating complex geometry into facade design and micro-scale material design.
A new geometric deep learning model called GFCN has been developed to detect stroke lesions in brain imaging scans. The model leverages rich geometric information to segment brain tissue and achieves higher segmentation performance than other neural network architectures.
Scientists developed a new model to simulate grid cells in non-Euclidean spaces, revealing heptagonal symmetry on a pseudospherical surface. This finding suggests that the brain may be able to encode non-conventional geometries and abstract spaces.