Hoodline

MIT Unveils MultiverSeg, A Groundbreaking AI System to Revolutionize Medical Image Segmentation

MIT researchers developed an AI tool, MultiverSeg, to simplify the annotation of medical images for clinical research.
IEEE

Analysis of Microscopic Data on the Behavior of Metallic Nickel Ore During Magnetic Enrichment Using SAM2 and Tensor Decomposition-Based Zero-Shot Image Segmentation

Abstract: The accurate separation and classification of minerals are crucial for integrating deep learning-based computer vision approaches into mineral enrichment processes. In this work, labeled ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...
Medical Xpress

Semi-supervised segmentation method developed for 3D medical image accuracy

A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
IEEE

Integration of K-Means and SVM for Customer Segmentation Based on Customer Behaviour Using LRFM and Product Preference

Abstract: In the era of Big Data, utilizing customer transaction data in the retail industry across various sectors has become crucial for understanding customer behavior and optimizing marketing ...