Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence

被引：11

作者：

Gorelik, Natalia ^{[1
]}

Chong, Jaron ^{[1
]}

Lin, Dana J. ^{[2
]}

机构：

[1] McGill Univ, Dept Diagnost Radiol, Hlth Ctr, Montreal, PQ, Canada

[2] NYU Langone Hlth, Div Musculoskeletal Radiol, Dept Radiol, 301 East 17th St,6th Floor, New York, NY 10003 USA

来源：

SEMINARS IN MUSCULOSKELETAL RADIOLOGY | 2020年 / 24卷 / 01期

关键词：

musculoskeletal; deep learning; neural network; COMPUTER-AIDED DETECTION; AUTOMATED DETECTION; TEMPORAL SUBTRACTION; VERTEBRAL FRACTURES; THORACOLUMBAR SPINE; CT; DIAGNOSIS; MODEL; CLASSIFICATION; METASTASES;

D O I：

10.1055/s-0039-3400266

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have been studied, including the diagnosis of bone tumors, detection of osseous metastases, assessment of bone age, identification of fractures, and detection and grading of osteoarthritis. This article explores the applications of AI for image interpretation of MSK pathologies.

引用

页码：38 / 49

页数：12

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