The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset.

IF 8.1 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Radiology-Artificial Intelligence Pub Date : 2024-11-01 DOI:10.1148/ryai.240101

Jeffrey D Rudie, Hui-Ming Lin, Robyn L Ball, Sabeena Jalal, Luciano M Prevedello, Savvas Nicolaou, Brett S Marinelli, Adam E Flanders, Kirti Magudia, George Shih, Melissa A Davis, John Mongan, Peter D Chang, Ferco H Berger, Sebastiaan Hermans, Meng Law, Tyler Richards, Jan-Peter Grunz, Andreas Steven Kunz, Shobhit Mathur, Sandro Galea-Soler, Andrew D Chung, Saif Afat, Chin-Chi Kuo, Layal Aweidah, Ana Villanueva Campos, Arjuna Somasundaram, Felipe Antonio Sanchez Tijmes, Attaporn Jantarangkoon, Leonardo Kayat Bittencourt, Michael Brassil, Ayoub El Hajjami, Hakan Dogan, Muris Becircic, Agrahara G Bharatkumar, Eduardo Moreno Júdice de Mattos Farina, Errol Colak

引用次数: 0

Abstract

Supplemental material is available for this article.

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RSNA 腹部创伤 CT (RATIC) 数据集。

"刚刚接受 "的论文经过同行评审，已被接受在《放射学》上发表：人工智能》上发表。这篇文章在以最终版本发表之前，还将经过校对、排版和校对审核。请注意，在制作最终校对稿的过程中，可能会发现影响内容的错误。RSNA 腹部创伤 CT (RATIC) 数据集包含 4,274 项与创伤相关的腹部 CT 研究注释，可在 https://imaging.rsna.org/dataset/5 和 https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection 上查阅。©RSNA，2024。

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

Radiology-Artificial Intelligence

CiteScore

16.20

自引率

1.00%

发文量

期刊介绍： Radiology: Artificial Intelligence is a bi-monthly publication that focuses on the emerging applications of machine learning and artificial intelligence in the field of imaging across various disciplines. This journal is available online and accepts multiple manuscript types, including Original Research, Technical Developments, Data Resources, Review articles, Editorials, Letters to the Editor and Replies, Special Reports, and AI in Brief.