Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...

Abstract: Hyperspectral imaging technology is considered a new paradigm for high-precision pathological image segmentation due to its ability to obtain spatial and spectral information of the detected ...

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...

Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

1 School of Biomedical Engineering, Sichuan University, Chengdu, China 2 National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...