AIMC Topic: Multiparametric Magnetic Resonance Imaging
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A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI.
Scientific reports
Jun 29, 2020
Multiparametric magnetic resonance imaging (mpMRI) has been shown to improve radiologists' performance in the clinical diagnosis of breast cancer. This machine learning study develops a deep transfer learning computer-aided diagnosis (CADx) methodolo...
Clinico-radiological characteristic-based machine learning in reducing unnecessary prostate biopsies of PI-RADS 3 lesions with dual validation.
European radiology
Jun 10, 2020
OBJECTIVE: To evaluate machine learning-based classifiers in detecting clinically significant prostate cancer (PCa) with Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions.
Validation Studies as Topic
Image-Guided Biopsy
Unnecessary Procedures
Multiparametric Magnetic Resonance Imaging
Radiography
Prostatic Neoplasms
Prostate-Specific Antigen
Prostate
Male
Middle Aged
Ultrasonography
Logistic Models
ROC Curve
Retrospective Studies
Support Vector Machine
Decision Trees
Reproducibility of Results
Area Under Curve
Aged
Humans
Aged, 80 and over
Machine Learning
Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study.
Journal of magnetic resonance imaging : JMRI
Jun 1, 2020
BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) of the prostate but suffers from high intra/interreader variability.
Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
European radiology
Mar 28, 2020
OBJECTIVES: We develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) in the classification of the pulmonary lesion and identify optimal machine learning methods.
Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.
Clinical neuroradiology
Feb 14, 2020
PURPOSE: Volumetric assessment of meningiomas represents a valuable tool for treatment planning and evaluation of tumor growth as it enables a more precise assessment of tumor size than conventional diameter methods. This study established a dedicate...
Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.
Breast cancer research and treatment
Feb 4, 2020
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...
Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.
Breast (Edinburgh, Scotland)
Nov 23, 2019
In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR), some achieve a partial response, and some do not respond at all or even progress. Accurate predicti...
Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.
European journal of radiology
Nov 20, 2019
PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.
Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization.
Medical image analysis
Oct 1, 2019
The availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially mul...
Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.
European radiology
Aug 29, 2019
OBJECTIVE: To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN).
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