A foundation model unlocks unified biomedical image analysis

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2024-11-18 DOI:10.1038/s41592-024-02519-9

Yuhao Huang, Haoran Dou, Dong Ni

引用次数: 0

Abstract

A groundbreaking biomedical AI foundation model, called BiomedParse, unifies detection, segmentation and recognition of organs, setting the stage for enhanced efficiency and accuracy in biomedical research and diagnostics.

Abstract Image

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一个基础模型开启了统一的生物医学图像分析。

一个突破性的生物医学人工智能基础模型，称为BiomedParse，将器官的检测、分割和识别统一起来，为提高生物医学研究和诊断的效率和准确性奠定了基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Methods 生物-生化研究方法

CiteScore

58.70

自引率

1.70%

发文量

326

审稿时长

1 months

期刊介绍： Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.