Automated Breast Lesion Detection and Characterization with the Wavelia Microwave Breast Imaging System: Methodological Proof-of-Concept on First-in-Human Patient Data
| Autor: | Angie Fasoula, Luc Duchesne, Julio Daniel Gil Cano, Brian M. Moloney, Sami M. Abd Elwahab, Michael J. Kerin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Applied Sciences, Vol 11, Iss 21, p 9998 (2021) |
| Druh dokumentu: | article |
| ISSN: | 11219998 2076-3417 |
| DOI: | 10.3390/app11219998 |
| Popis: | Microwave Breast Imaging (MBI) is an emerging non-ionizing imaging modality, with the potential to support breast diagnosis and management. Wavelia is an MBI system prototype, of 1st generation, which has recently completed a First-In-Human (FiH) clinical investigation on a 25-symptomatic patient cohort, to explore the capacity of the technology to detect and characterize malignant (invasive carcinoma) and benign (fibroadenoma, cyst) breast disease. Two recent publications presented promising results demonstrated by the device in this FiH study in detecting and localizing, as well as delineating size and malignancy risk, of malignant and benign palpable breast lesions. In this paper, the methodology that has been employed in the Wavelia semi-automated Quantitative Imaging Function (QIF), to support breast lesion detection and characterization in the FiH clinical investigation of the device, is presented and the critical design parameters are highlighted. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|