AI Medical Compendium Topic:
Contrast Media

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Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier.

Medical image analysis Oct 22, 2018
Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose an algorithm that extracts coronary artery centerlines in CCTA using a con...
Humans Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Netherlands Algorithms Coronary Vessels Retrospective Studies Computed Tomography Angiography Contrast Media
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Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.

European radiology Sep 25, 2018
OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.
Male Middle Aged Nomograms Support Vector Machine Female Risk Factors Aged Adult Adenoma Area Under Curve Cavernous Sinus Contrast Media Magnetic Resonance Imaging Neoplasm Invasiveness Pituitary Neoplasms Humans Retrospective Studies
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MRI-based automated detection of implanted low dose rate (LDR) brachytherapy seeds using quantitative susceptibility mapping (QSM) and unsupervised machine learning (ML).

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Sep 19, 2018
BACKGROUND AND PURPOSE: Permanent seed brachytherapy is an established treatment option for localized prostate cancer. Currently, post-implant dosimetry is performed on CT images despite challenging target delineation due to limited soft tissue contr...
Humans Radiotherapy Dosage Unsupervised Machine Learning Phantoms, Imaging Tomography, X-Ray Computed Prostatic Neoplasms Male Iodine Radioisotopes Contrast Media Brachytherapy Magnetic Resonance Imaging
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Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver.

Radiology Sep 4, 2018
Purpose To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver. Materials and Methods DLS for CT-based staging of liver fibrosis was created by using a development data set that included portal...
Contrast Media Liver Radiographic Image Enhancement Middle Aged Severity of Illness Index Deep Learning Liver Cirrhosis Humans Tomography, X-Ray Computed Female Reproducibility of Results Adult Male
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Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.

AJR. American journal of roentgenology May 24, 2018
OBJECTIVE: The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers.
Sensitivity and Specificity Breast Neoplasms Middle Aged Cone-Beam Computed Tomography Contrast Media Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Iohexol Humans Machine Learning Prospective Studies Female
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

Magnetic resonance in medicine May 17, 2018
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...
Signal-To-Noise Ratio Protons Male Aged Middle Aged Humans Image Processing, Computer-Assisted Aged, 80 and over Deep Learning Algorithms Contrast Media Young Adult Adolescent Databases, Factual Magnetic Resonance Imaging Adult Female Models, Statistical
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Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine May 16, 2018
PURPOSE: Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classificatio...
Contrast Media Magnetic Resonance Imaging Diagnosis, Differential Glioblastoma Image Interpretation, Computer-Assisted Central Nervous System Neoplasms Retrospective Studies ROC Curve Support Vector Machine Lymphoma Humans Machine Learning
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A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection.

IEEE/ACM transactions on computational biology and bioinformatics May 11, 2018
The important role of angiogenesis in cancer development has driven many researchers to investigate the prospects of noninvasive cancer diagnosis based on the technology of contrast-enhanced ultrasound (CEUS) imaging. This paper presents a deep learn...
Area Under Curve Prostatic Neoplasms Humans Video Recording Neural Networks, Computer Neoplasm Transplantation Algorithms Reproducibility of Results Image Processing, Computer-Assisted Sensitivity and Specificity Computational Biology Male Contrast Media Deep Learning Models, Statistical Ultrasonography
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Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Medical image analysis Mar 27, 2018
Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate qu...
Computed Tomography Angiography Radiographic Image Interpretation, Computer-Assisted Humans Thrombosis Neural Networks, Computer Artifacts Contrast Media Aortic Aneurysm, Abdominal Pattern Recognition, Automated
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Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.

Medical physics Mar 25, 2018
PURPOSE: To develop an automatic deep feature classification (DFC) method for distinguishing benign angiomyolipoma without visible fat (AMLwvf) from malignant clear cell renal cell carcinoma (ccRCC) from abdominal contrast-enhanced computer tomograph...
Kidney Neoplasms Humans Sensitivity and Specificity Carcinoma, Renal Cell Machine Learning Radiography, Abdominal Image Processing, Computer-Assisted Contrast Media Tomography, X-Ray Computed Diagnosis, Differential Angiomyolipoma
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