AIMC Topic: Multiparametric Magnetic Resonance Imaging
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Deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram for predicting Ki-67 expression in rectal cancer.
Abdominal radiology (New York)
Mar 15, 2024
PURPOSE: To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram in predicting the Ki-67 expression in rectal cancer.
Fully Automated Identification of Lymph Node Metastases and Lymphovascular Invasion in Endometrial Cancer From Multi-Parametric MRI by Deep Learning.
Journal of magnetic resonance imaging : JMRI
Mar 12, 2024
BACKGROUND: Early and accurate identification of lymphatic node metastasis (LNM) and lymphatic vascular space invasion (LVSI) for endometrial cancer (EC) patients is important for treatment design, but difficult on multi-parametric MRI (mpMRI) images...
Deep Learning
ROC Curve
Image Processing, Computer-Assisted
Lymph Nodes
Retrospective Studies
Aged
Female
Adult
Image Interpretation, Computer-Assisted
Humans
Middle Aged
Endometrial Neoplasms
Lymphatic Metastasis
Magnetic Resonance Imaging
Diffusion Magnetic Resonance Imaging
Neoplasm Invasiveness
Multiparametric Magnetic Resonance Imaging
Deep learning model for the detection of prostate cancer and classification of clinically significant disease using multiparametric MRI in comparison to PI-RADs score.
Urologic oncology
Feb 22, 2024
BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) is an established reporting scheme for multiparametric magnetic resonance imaging (mpMRI) to distinguish clinically significant prostate cancer (csPCa). Deep learning (DL) holds gre...
Breast cancer molecular subtype prediction: Improving interpretability of complex machine-learning models based on multiparametric-MRI features using SHapley Additive exPlanations (SHAP) methodology.
Diagnostic and interventional imaging
Feb 16, 2024
Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.
Diagnostic and interventional imaging
Jan 24, 2024
PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis.
Multiparametric MRI-Based Machine Learning Models for the Characterization of Cystic Renal Masses Compared to the Bosniak Classification, Version 2019: A Multicenter Study.
Academic radiology
Jan 19, 2024
RATIONALE AND OBJECTIVE: Accurate differentiation between benign and malignant cystic renal masses (CRMs) is challenging in clinical practice. This study aimed to develop MRI-based machine learning models for differentiating between benign and malign...
Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.
European radiology
Oct 18, 2023
OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicting human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.
Journal of neuroradiology = Journal de neuroradiologie
Aug 29, 2023
PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (GBM), intracranial metastatic disease (IMD) and primary CNS lymphoma (PCNSL).
Deep learning based on dynamic susceptibility contrast MR imaging for prediction of local progression in adult-type diffuse glioma (grade 4).
Scientific reports
Aug 24, 2023
Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross total resection of contrast-enhancing lesions. Cerebral blood volu...
Deep Learning-Based Multiparametric MRI Model for Preoperative T-Stage in Rectal Cancer.
Journal of magnetic resonance imaging : JMRI
Jun 27, 2023
BACKGROUND: Conventional MRI staging can be challenging in the preoperative assessment of rectal cancer. Deep learning methods based on MRI have shown promise in cancer diagnosis and prognostication. However, the value of deep learning in rectal canc...
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