Cargando…
Subcategorization of suspicious non-mass-like enhancement lesions(BI-RADS-MRI Category4)
BACKGROUND: This study aims to providing a reliable method that has good compliance and is easy to master to improve the accuracy of NMLE diagnosis. METHODS: This study retrospectively analyzed 122 cases of breast non-mass-like enhancement (NMLE) lesions confirmed by postoperative histology. MRI fea...
Autores principales: | Liu, Dandan, Ba, Zhaogui, Gao, Yan, Wang, Linhong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636905/ https://www.ncbi.nlm.nih.gov/pubmed/37950164 http://dx.doi.org/10.1186/s12880-023-01144-w |
Ejemplares similares
-
Apparent Diffusion Coefficient to Subdivide Breast Imaging Reporting and Data System Magnetic Resonance Imaging (BI-RADS-MRI) Category 4 Lesions
por: Liu, Dandan, et al.
Publicado: (2018) -
Subcategorization of intermediate suspicion thyroid nodules based on suspicious ultrasonographic findings
por: Kim, Haejung, et al.
Publicado: (2023) -
Predictive performance of BI-RADS magnetic resonance imaging
descriptors in the context of suspicious (category 4) findings
por: de Almeida, João Ricardo Maltez, et al.
Publicado: (2016) -
A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses
por: Interlenghi, Matteo, et al.
Publicado: (2022) -
Diffusion-weighted imaging of suspicious (BI-RADS 4) breast lesions:
stratification based on histopathology
por: de Almeida, João Ricardo Maltez, et al.
Publicado: (2017)