دورية أكاديمية
Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: AJR Expert Panel Narrative Review.
| العنوان: | Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: AJR Expert Panel Narrative Review. |
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| المؤلفون: | Yi PH; University of Maryland Medical Intelligent Imaging Center, University of Maryland School of Medicine, Baltimore, MD.; Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD., Garner HW; Department of Radiology, Mayo Clinic Florida, Jacksonville, FL., Hirschmann A; Imamed Radiology Nordwest, Basel, Switzerland.; Department of Radiology, University of Basel, Basel, Switzerland., Jacobson JA; Lenox Hill Radiology, New York, NY.; Department of Radiology, University of California, San Diego Medical Center, San Diego, CA., Omoumi P; Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland.; Department of Radiology, University of Lausanne, Lausanne, Switzerland., Oh K; Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea., Zech JR; Department of Radiology, Columbia University Irving Medical Center, New York-Presbyterian Hospital, New York, NY., Lee YH; Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea. |
| المصدر: | AJR. American journal of roentgenology [AJR Am J Roentgenol] 2024 Mar; Vol. 222 (3), pp. e2329530. Date of Electronic Publication: 2023 Jul 12. |
| نوع المنشور: | Journal Article; Review |
| اللغة: | English |
| بيانات الدورية: | Publisher: American Roentgen Ray Society Country of Publication: United States NLM ID: 7708173 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-3141 (Electronic) Linking ISSN: 0361803X NLM ISO Abbreviation: AJR Am J Roentgenol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: <2004-> : Leesburg, VA : American Roentgen Ray Society Original Publication: Springfield, Ill., Thomas. |
| مواضيع طبية MeSH: | Artificial Intelligence* , Tendons*, Humans ; Ultrasonography ; Algorithms ; Head |
| مستخلص: | Artificial intelligence (AI) is increasingly used in clinical practice for musculoskeletal imaging tasks, such as disease diagnosis and image reconstruction. AI applications in musculoskeletal imaging have focused primarily on radiography, CT, and MRI. Although musculoskeletal ultrasound stands to benefit from AI in similar ways, such applications have been relatively underdeveloped. In comparison with other modalities, ultrasound has unique advantages and disadvantages that must be considered in AI algorithm development and clinical translation. Challenges in developing AI for musculoskeletal ultrasound involve both clinical aspects of image acquisition and practical limitations in image processing and annotation. Solutions from other radiology subspecialties (e.g., crowdsourced annotations coordinated by professional societies), along with use cases (most commonly rotator cuff tendon tears and palpable soft-tissue masses), can be applied to musculoskeletal ultrasound to help develop AI. To facilitate creation of high-quality imaging datasets for AI model development, technologists and radiologists should focus on increasing uniformity in musculoskeletal ultrasound performance and increasing annotations of images for specific anatomic regions. This Expert Panel Narrative Review summarizes available evidence regarding AI's potential utility in musculoskeletal ultrasound and challenges facing its development. Recommendations for future AI advancement and clinical translation in musculoskeletal ultrasound are discussed. |
| فهرسة مساهمة: | Keywords: artificial intelligence; musculoskeletal; ultrasound |
| تواريخ الأحداث: | Date Created: 20230712 Date Completed: 20240411 Latest Revision: 20240529 |
| رمز التحديث: | 20240529 |
| DOI: | 10.2214/AJR.23.29530 |
| PMID: | 37436032 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1546-3141 |
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| DOI: | 10.2214/AJR.23.29530 |