AIMC Topic: Parenchymal Tissue

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Intervening Nidal Brain Parenchyma and Risk of Radiation-Induced Changes After Radiosurgery for Brain Arteriovenous Malformation: A Study Using an Unsupervised Machine Learning Algorithm.

World neurosurgery Jan 22, 2019
OBJECTIVE: To assess the sensitivity and specificity of arteriovenous malformation (AVM) nidal component identification and quantification using an unsupervised machine learning algorithm and to evaluate the association between intervening nidal brai...
Humans Algorithms Prospective Studies Brain Female Risk Factors Aged Young Adult Adult Male Middle Aged Adolescent Child Unsupervised Machine Learning Radiosurgery Radiation Injuries Intracranial Arteriovenous Malformations Parenchymal Tissue
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Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology Feb 1, 2018
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.
Humans Neural Networks, Computer Retrospective Studies Female Adult Breast Neoplasms Case-Control Studies ROC Curve Mammography Area Under Curve Breast Parenchymal Tissue
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Classification of Background Parenchymal Uptake on Molecular Breast Imaging Using a Convolutional Neural Network.

JCO clinical cancer informatics Feb 1, 2019
PURPOSE: Background parenchymal uptake (BPU), which describes the level of radiotracer uptake in normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor. Our objective was to develop and vali...
Humans Neural Networks, Computer Algorithms Female Risk Factors Breast Neoplasms Risk Assessment Mammography Breast Radiopharmaceuticals Molecular Imaging Image Interpretation, Computer-Assisted Radionuclide Imaging Parenchymal Tissue
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