Evolving and Novel Applications of Artificial Intelligence in Abdominal Imaging.

IF 2.2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Tomography Pub Date : 2024-11-18 DOI:10.3390/tomography10110133

Mark R Loper, Mina S Makary

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引用次数: 0

Abstract

Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal radiology, leading to an improvement in diagnostic and disease management capabilities. This narrative review seeks to evaluate the current standing of AI in abdominal imaging, with a focus on recent literature contributions. This work explores the diagnosis and characterization of hepatobiliary, pancreatic, gastric, colonic, and other pathologies. In addition, the role of AI has been observed to help differentiate renal, adrenal, and splenic disorders. Furthermore, workflow optimization strategies and quantitative imaging techniques used for the measurement and characterization of tissue properties, including radiomics and deep learning, are highlighted. An assessment of how these advancements enable more precise diagnosis, tumor description, and body composition evaluation is presented, which ultimately advances the clinical effectiveness and productivity of radiology. Despite the advancements of AI in abdominal imaging, technical, ethical, and legal challenges persist, and these challenges, as well as opportunities for future development, are highlighted.

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人工智能在腹部成像中不断发展的新应用。

人工智能（AI）的进步极大地改变了腹部放射学领域，提高了诊断和疾病管理能力。这篇叙述性综述旨在评估人工智能在腹部成像领域的现状，重点关注近期的文献贡献。这些作品探讨了肝胆、胰腺、胃、结肠和其他病变的诊断和定性。此外，还观察到人工智能在帮助区分肾脏、肾上腺和脾脏疾病方面的作用。此外，还重点介绍了用于测量和表征组织特性的工作流程优化策略和定量成像技术，包括放射组学和深度学习。报告评估了这些先进技术如何实现更精确的诊断、肿瘤描述和身体成分评估，最终提高放射学的临床效率和生产力。尽管人工智能在腹部成像方面取得了进步，但技术、伦理和法律方面的挑战依然存在，本文重点介绍了这些挑战以及未来发展的机遇。

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

Tomography Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

2.70

自引率

10.50%

发文量

222

期刊介绍： TomographyTM publishes basic (technical and pre-clinical) and clinical scientific articles which involve the advancement of imaging technologies. Tomography encompasses studies that use single or multiple imaging modalities including for example CT, US, PET, SPECT, MR and hyperpolarization technologies, as well as optical modalities (i.e. bioluminescence, photoacoustic, endomicroscopy, fiber optic imaging and optical computed tomography) in basic sciences, engineering, preclinical and clinical medicine. Tomography also welcomes studies involving exploration and refinement of contrast mechanisms and image-derived metrics within and across modalities toward the development of novel imaging probes for image-based feedback and intervention. The use of imaging in biology and medicine provides unparalleled opportunities to noninvasively interrogate tissues to obtain real-time dynamic and quantitative information required for diagnosis and response to interventions and to follow evolving pathological conditions. As multi-modal studies and the complexities of imaging technologies themselves are ever increasing to provide advanced information to scientists and clinicians. Tomography provides a unique publication venue allowing investigators the opportunity to more precisely communicate integrated findings related to the diverse and heterogeneous features associated with underlying anatomical, physiological, functional, metabolic and molecular genetic activities of normal and diseased tissue. Thus Tomography publishes peer-reviewed articles which involve the broad use of imaging of any tissue and disease type including both preclinical and clinical investigations. In addition, hardware/software along with chemical and molecular probe advances are welcome as they are deemed to significantly contribute towards the long-term goal of improving the overall impact of imaging on scientific and clinical discovery.