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Literature DB >> 31166761

Artificial Intelligence in Musculoskeletal Imaging: Current Status and Future Directions.

Soterios Gyftopoulos^1,2, Dana Lin¹, Florian Knoll¹, Ankur M Doshi¹, Tatiane Cantarelli Rodrigues¹, Michael P Recht¹.

Abstract

OBJECTIVE. The objective of this article is to show how artificial intelligence (AI) has impacted different components of the imaging value chain thus far as well as to describe its potential future uses. CONCLUSION. The use of AI has the potential to greatly enhance every component of the imaging value chain. From assessing the appropriateness of imaging orders to helping predict patients at risk for fracture, AI can increase the value that musculoskeletal imagers provide to their patients and to referring clinicians by improving image quality, patient centricity, imaging efficiency, and diagnostic accuracy.

Entities: Disease Gene Species

Keywords: MRI; artificial intelligence; deep learning; fast MRI; machine learning; musculoskeletal imaging

Mesh：

Year: 2019 PMID： 31166761 PMCID： PMC6706287 DOI： 10.2214/AJR.19.21117

Source DB: PubMed Journal: AJR Am J Roentgenol ISSN： 0361-803X Impact factor: 3.959

52 in total

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9. Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry.

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17 in total

1. Artificial intelligence in musculoskeletal oncological radiology.

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Review 4. Current understanding on artificial intelligence and machine learning in orthopaedics - A scoping review.

Authors: Vishal Kumar; Sandeep Patel; Vishnu Baburaj; Aditya Vardhan; Prasoon Kumar Singh; Raju Vaishya
Journal: J Orthop Date: 2022-08-26

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