Cargando…

Deep Learning for Classification of Bone Lesions on Routine MRI

BACKGROUND: Radiologists have difficulty distinguishing benign from malignant bone lesions because these lesions may have similar imaging appearances. The purpose of this study was to develop a deep learning algorithm that can differentiate benign and malignant bone lesions using routine magnetic re...

Descripción completa

Detalles Bibliográficos
Autores principales:	Eweje, Feyisope R., Bao, Bingting, Wu, Jing, Dalal, Deepa, Liao, Wei-hua, He, Yu, Luo, Yongheng, Lu, Shaolei, Zhang, Paul, Peng, Xianjing, Sebro, Ronnie, Bai, Harrison X., States, Lisa
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2021
Materias:	Research Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190437/ https://www.ncbi.nlm.nih.gov/pubmed/34098339 http://dx.doi.org/10.1016/j.ebiom.2021.103402

Ejemplares similares

Deep learning-based classification of primary bone tumors on radiographs: A preliminary study
por: He, Yu, et al.
Publicado: (2020)

Translatability Analysis of National Institutes of Health–Funded Biomedical Research That Applies Artificial Intelligence
por: Eweje, Feyisope R., et al.
Publicado: (2022)

Positron emission tomography/computed tomography imaging appearance of benign and classic “do not touch” osseous lesions
por: Elangovan, Stacey M, et al.
Publicado: (2019)

FDG PET/CT evaluation of pathologically proven pulmonary lesions in an area of high endemic granulomatous disease
por: Sebro, Ronnie, et al.
Publicado: (2013)

Radiomic features from MRI distinguish myxomas from myxofibrosarcomas
por: Martin-Carreras, Teresa, et al.
Publicado: (2019)

Statistical estimation of deltoid subcutaneous fat pad thickness: implications for needle length for vaccination
por: Sebro, Ronnie
Publicado: (2022)

An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data
por: Kim, Chris K., et al.
Publicado: (2022)

An Important and Often Ignored Turnaround Time in Radiology – Clinician Turnaround Time: Implications for Musculoskeletal Radiology
por: Mayer, Michael, et al.
Publicado: (2019)

A Statistical Approach Regarding the Diagnosis of Osteoporosis and Osteopenia From DXA: Are We Underdiagnosing Osteoporosis?
por: Sebro, Ronnie, et al.
Publicado: (2021)

Utility of absolute apparent diffusion coefficient and chemical‐shift imaging versus CT attenuation for predicting malignancy from percutaneous bone biopsies
por: Sebro, Ronnie, et al.
Publicado: (2021)

Does NIH funding differ between medical specialties? A longitudinal analysis of NIH grant data by specialty and type of grant, 2011–2020
por: Schlafly, Andrew, et al.
Publicado: (2022)

Radiomics analysis in medical imaging research
por: Elmahdy, Mahmoud, et al.
Publicado: (2023)

Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study
por: Jiao, Zhicheng, et al.
Publicado: (2021)

Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification
por: Fusco, Roberta, et al.
Publicado: (2015)

Declining racial and ethnic representation in clinical academic medicine: A longitudinal study of 16 US medical specialties
por: Lett, Elle, et al.
Publicado: (2018)

Malignant Transformation of Recurrent Synovial Chondromatosis: A Case Report and Review
por: Urwin, John W, et al.
Publicado: (2019)

Machine Learning for Opportunistic Screening for Osteoporosis from CT Scans of the Wrist and Forearm
por: Sebro, Ronnie, et al.
Publicado: (2022)

Correction: Sebro, R.; De la Garza-Ramos, C. Machine Learning for Opportunistic Screening for Osteoporosis from CT Scans of the Wrist and Forearm. Diagnostics 2022, 12, 691
por: Sebro, Ronnie, et al.
Publicado: (2022)

Support vector machines are superior to principal components analysis for selecting the optimal bones’ CT attenuations for opportunistic screening for osteoporosis using CT scans of the foot or ankle
por: Sebro, Ronnie, et al.
Publicado: (2022)

Advantage of Adding Diffusion Weighted Imaging to Routine MRI Examinations in the Diagnostics of Scrotal Lesions
por: Algebally, Ahmed Mohamed, et al.
Publicado: (2015)

Willingness to use a wearable device capable of detecting and reversing overdose among people who use opioids in Philadelphia
por: Kanter, Katie, et al.
Publicado: (2021)

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions
por: White, Richard D., et al.
Publicado: (2022)

Automatic classification of focal liver lesions based on MRI and risk factors
por: Jansen, Mariëlle J. A., et al.
Publicado: (2019)

Imaging and histological appearance of pleomorphic hyalinizing angiectatic tumors: A case series and literature review
por: Jaramillo, Couger Jimenez, et al.
Publicado: (2018)

Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI
por: Stoyanova, Radka, et al.
Publicado: (2023)

Structured mating: Patterns and implications
por: Sebro, Ronnie, et al.
Publicado: (2017)

A systematic genotype and subgenotype re-ranking of hepatitis B virus under a novel classification standard
por: Yin, Yonghua, et al.
Publicado: (2019)

Differentiation of low and high grade renal cell carcinoma on routine MRI with an externally validated automatic machine learning algorithm
por: Purkayastha, Subhanik, et al.
Publicado: (2020)

A Rare Case of an Osteolytic Bone-infarct-associated Osteosarcoma: Case Report with Radiographic and Histopathologic Correlation, and Literature Review
por: McDonald, Michael D, et al.
Publicado: (2018)

Primary malignant perivascular epithelioid cell neoplasm (PEComa) of the bone mimicking granular cell tumor in core biopsy: A case report and literature review
por: Sadigh, Sam, et al.
Publicado: (2018)

Phase I and phase II clinical trials in sarcoma: Implications for drug discovery and development
por: Lee, Daniel Y., et al.
Publicado: (2019)

Not getting in too deep: A practical deep learning approach to routine crystallisation image classification
por: Milne, Jamie, et al.
Publicado: (2023)

Trends in Racial/Ethnic Representation Among US Medical Students
por: Lett, Elle, et al.
Publicado: (2019)

Measuring Deltoid Insufficiency after Supination-External Rotation Ankle Fracture with Lateral Talar Subluxation on Gravity Stress View
por: Haupt, Edward T., et al.
Publicado: (2022)

Chronic liver disease not a significant comorbid condition for COVID-19
por: Lin, Jiahao, et al.
Publicado: (2021)

A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions
por: Woitek, Ramona, et al.
Publicado: (2017)

Safety of routine early MRI in preterm infants
por: Plaisier, Annemarie, et al.
Publicado: (2012)

Automatic segmentation and classification of breast lesions through identification of informative multiparametric PET/MRI features
por: Vogl, Wolf-Dieter, et al.
Publicado: (2019)

Classification of Breast Lesions on DCE-MRI Data Using a Fine-Tuned MobileNet
por: Wang, Long, et al.
Publicado: (2023)

Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI
por: Laukamp, Kai Roman, et al.
Publicado: (2018)

Cannot write session to /tmp/vufind_sessions/sess_nngn693ldb6v50bon3067giklf