Cargando…

Prospective assessment of breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics

INTRODUCTION: AI-assisted ultrasound diagnosis is considered a fast and accurate new method that can reduce the subjective and experience-dependent nature of handheld ultrasound. In order to meet clinical diagnostic needs better, we first proposed a breast lesions AI classification model based on ul...

Descripción completa

Detalles Bibliográficos
Autores principales:	Qiu, Shunmin, Zhuang, Shuxin, Li, Bin, Wang, Jinhong, Zhuang, Zhemin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2023
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656688/ https://www.ncbi.nlm.nih.gov/pubmed/38023255 http://dx.doi.org/10.3389/fonc.2023.1274557

Ejemplares similares

Non-mass lesions on breast ultrasound: why does not the ACR BI-RADS breast ultrasound lexicon add the terminology?
por: Uematsu, Takayoshi
Publicado: (2023)

An RDAU-NET model for lesion segmentation in breast ultrasound images
por: Zhuang, Zhemin, et al.
Publicado: (2019)

Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks
por: Sexauer, Raphael, et al.
Publicado: (2023)

Contrast-Enhanced Ultrasound in the Differential Diagnosis and Risk Stratification of ACR TI-RADS Category 4 and 5 Thyroid Nodules With Non-Hypovascular
por: Wang, Yanfang, et al.
Publicado: (2021)

Contrast-enhanced ultrasound and shear wave elastography in the diagnosis of ACR TI-RADS 4 and 5 category thyroid nodules coexisting with Hashimoto’s thyroiditis
por: Wang, Bin, et al.
Publicado: (2023)

Deep Learning Based on ACR TI-RADS Can Improve the Differential Diagnosis of Thyroid Nodules
por: Wu, Ge-Ge, et al.
Publicado: (2021)

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer
por: Pan, Qiao-Hong, et al.
Publicado: (2023)

Observer Agreement Using the ACR Breast Imaging Reporting and Data System (BI-RADS)-Ultrasound, First Edition (2003)
por: Park, Chang Suk, et al.
Publicado: (2007)

A National Chinese Survey on Ultrasound Feature Interpretation and Risk Assessment of Breast Masses Under ACR BI-RADS
por: Wen, Wen, et al.
Publicado: (2021)

Interobserver concordance in the BI-RADS classification of breast ultrasound exams
por: Calas, Maria Julia G, et al.
Publicado: (2012)

An MRI-Based Radiomics Model for Predicting the Benignity and Malignancy of BI-RADS 4 Breast Lesions
por: Zhang, Renzhi, et al.
Publicado: (2022)

The Diagnostic Role of Computed Tomography for ACR TI-RADS 4–5 Thyroid Nodules With Coarse Calcifications
por: Wei, Peiying, et al.
Publicado: (2020)

Agreement in breast lesion assessment and final BI-RADS classification between radial and meander-like breast ultrasound
por: Brasier-Lutz, Pascale, et al.
Publicado: (2021)

Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
por: Lin, Mingnan, et al.
Publicado: (2022)

Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment
por: Hao, Wen, et al.
Publicado: (2020)

BI-RADS Reading of Non-Mass Lesions on DCE-MRI and Differential Diagnosis Performed by Radiomics and Deep Learning
por: Zhou, Jiejie, et al.
Publicado: (2021)

Evaluation of diagnostic efficacy of multimode ultrasound in BI-RADS 4 breast neoplasms and establishment of a predictive model
por: Chen, Yunhao, et al.
Publicado: (2022)

Multiparameter MRI Model With DCE-MRI, DWI, and Synthetic MRI Improves the Diagnostic Performance of BI-RADS 4 Lesions
por: Sun, Shi Yun, et al.
Publicado: (2021)

A Comparative Assessment of MR BI-RADS 4 Breast Lesions With Kaiser Score and Apparent Diffusion Coefficient Value
por: Meng, Lingsong, et al.
Publicado: (2021)

Downgrade BI-RADS 4A Patients Using Nomogram Based on Breast Magnetic Resonance Imaging, Ultrasound, and Mammography
por: Xie, Yamie, et al.
Publicado: (2022)

Comparison of Diagnostic Performance of Five Different Ultrasound TI-RADS Classification Guidelines for Thyroid Nodules
por: Yang, Ruoning, et al.
Publicado: (2020)

The 2017 ACR TI-RADS: pictorial essay
por: Pires, André Tojal, et al.
Publicado: (2022)

Combined Use of Shear Wave Elastography, Microvascular Doppler Ultrasound Technique, and BI-RADS for the Differentiation of Benign and Malignant Breast Masses
por: Wang, Bin, et al.
Publicado: (2022)

Nomograms for prediction of breast cancer in breast imaging reporting and data system (BI-RADS) ultrasound category 4 or 5 lesions: A single-center retrospective study based on radiomics features
por: Hong, Zhi-Liang, et al.
Publicado: (2022)

Evaluation of Contrast-Enhanced Mammography and Development of Flowchart for BI-RADS Classification of Breast Lesions
por: Klarić, Kristina, et al.
Publicado: (2023)

Prospective evaluation of contrast-enhanced ultrasound of breast BI-RADS 3–5 lesions
por: Janu, Eva, et al.
Publicado: (2020)

Concordance of the ACR TI-RADS Classification With Bethesda Scoring and Histopathology Risk Stratification of Thyroid Nodules
por: Huang, Elaine Y. F., et al.
Publicado: (2023)

ACR’s Connect and AI-LAB technical framework
por: Brink, Laura, et al.
Publicado: (2022)

Ultrasound Radiomics Nomogram to Diagnose Sub-Centimeter Thyroid Nodules Based on ACR TI-RADS
por: Lu, Wenwu, et al.
Publicado: (2022)

Diagnostic value of ACR TI-RADS combined with three-dimensional shear wave elastography in ACR TI-RADS 4 and 5 thyroid nodules
por: Hao, Lijun, et al.
Publicado: (2023)

Analysis of 665 thyroid nodules using both EU-TIRADS and ACR TI-RADS classification systems
por: Borges, Ana Paula, et al.
Publicado: (2023)

Ultrasound real-time elastography can predict malignancy in BI-RADS(®)-US 3 lesions
por: Wojcinski, Sebastian, et al.
Publicado: (2013)

Superb Microvascular Imaging Technology Can Improve the Diagnostic Efficiency of the BI-RADS System
por: Cai, Siman, et al.
Publicado: (2021)

Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS
por: Luo, Wei-quan, et al.
Publicado: (2019)

Structural basis for inhibition of the type I-F CRISPR–Cas surveillance complex by AcrIF4, AcrIF7 and AcrIF14
por: Gabel, Clinton, et al.
Publicado: (2020)

Synthetic MRI, multiplexed sensitivity encoding, and BI-RADS for benign and malignant breast cancer discrimination
por: Liu, Jinrui, et al.
Publicado: (2023)

Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies
por: Lyu, Yidong, et al.
Publicado: (2023)

Multi-Features-Based Automated Breast Tumor Diagnosis Using Ultrasound Image and Support Vector Machine
por: Zhuang, Zhemin, et al.
Publicado: (2021)

Comparison of Danish dichotomous and BI-RADS classifications of mammographic density
por: Hodge, Rebecca, et al.
Publicado: (2014)

Artificial intelligence breast ultrasound and handheld ultrasound in the BI-RADS categorization of breast lesions: A pilot head to head comparison study in screening program
por: Huang, Xiaoxi, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_ceucealh2hdmhfspoc013sqb09