Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers
AI using YOLOv11 allowed us to discriminate reliably between HA and SO using different complexity high-frequency US devices and operators. Further AI DL-specific work is needed to identify CaHA and PMMA more accurately.
Authors
- Patricia Barrera (ORCID: https://orcid.org/0000-0001-7222-9793)
- Leonie Schelke (ORCID: https://orcid.org/0000-0002-5512-1956)
- Julia Diva Zavariz (ORCID: https://orcid.org/0000-0002-5536-9513)
- Rosa Sigrist (ORCID: https://orcid.org/0000-0002-5780-4136)
- Cláudia Borges Fontan Câmara (ORCID: https://orcid.org/0000-0002-9687-425X)
- Francisco Javier Rodríguez‐Gómez (ORCID: https://orcid.org/0000-0002-7027-6569)
- Luciana Zattar-Ramos (ORCID: https://orcid.org/0000-0002-5229-8596)
- Ximena Wortsman (ORCID: https://orcid.org/0000-0003-3359-5023)
- Juliana Paulos de Rezende (ORCID: https://orcid.org/0009-0008-3737-9890)
- Claudia González (ORCID: https://orcid.org/0000-0003-2618-308X)
- Peter J. Velthuis (ORCID: https://orcid.org/0000-0002-9449-0068)
- Manuel Lozano (ORCID: https://orcid.org/0000-0002-2188-7486)
- Gabriela Ortiz‐Orellana
- Yessenia Valderrama
- Francisco de Cabo
- Eliza Porciuncula Justo Ducati
Institutions
- University of Miami (US)
- Pontificia Universidad Católica de Chile (CL)
- Universidad de Granada (ES)
- Erasmus MC (NL)
- Hospital Universitário Gaffrée e Guinle (BR)
- Institute for Diagnostic Imaging and Research of the Skin and Soft Tissues (CL)
- Centro de Investigación Biomédica en Red (ES)
- Associação Paulista para o Desenvolvimento da Medicina (BR)
- Ultrasonic Technologies (United States) (US)
- University and Rehabilitation Clinics Ulm (DE)
- Universidad Autónoma de Entre Ríos (AR)
- Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (BR)
- Hospital Sírio-Libanês (BR)
- Sociedade Brasileira de Cardiologia (BR)
- Universidad Nacional de Entre Ríos (AR)
- University of Chile (CL)
Publication Details
- Journal
- Journal of Ultrasound in Medicine
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1002/jum.70079
- Citations
- 1
- Primary Topic
- Dermatologic Treatments and Research
- Type
- article
- Field-Weighted Citation Impact
- 2.00