AIMC Journal:
Academic radiology

Showing 281 to 290 of 317 articles

Quantitative and Qualitative Evaluation of Convolutional Neural Networks with a Deeper U-Net for Sparse-View Computed Tomography Reconstruction.

Academic radiology Jul 4, 2019
RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction.
Tomography, X-Ray Computed Reproducibility of Results Image Processing, Computer-Assisted Signal-To-Noise Ratio Neural Networks, Computer
View on PubMed DOI

Automated Identification of Optimal Portal Venous Phase Timing with Convolutional Neural Networks.

Academic radiology May 28, 2019
OBJECTIVES: To develop a deep learning-based algorithm to automatically identify optimal portal venous phase timing (PVP-timing) so that image analysis techniques can be accurately performed on post contrast studies.
Portal Vein Clinical Trials as Topic Humans Neural Networks, Computer Algorithms Retrospective Studies Deep Learning Liver Neoplasms Contrast Media
View on PubMed DOI

Grading of Clear Cell Renal Cell Carcinomas by Using Machine Learning Based on Artificial Neural Networks and Radiomic Signatures Extracted From Multidetector Computed Tomography Images.

Academic radiology May 27, 2019
RATIONALE AND OBJECTIVES: To evaluate the ability of artificial neural networks (ANN) fed with radiomic signatures (RSs) extracted from multidetector computed tomography images in differentiating the histopathological grades of clear cell renal cell ...
Neural Networks, Computer Machine Learning Retrospective Studies Diagnosis, Differential Humans Kidney Neoplasms Multidetector Computed Tomography Carcinoma, Renal Cell
View on PubMed DOI

Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study.

Academic radiology Apr 30, 2019
RATIONALE AND OBJECTIVES: Intravenous thrombolysis decision-making and obtaining of consent would be assisted by an individualized risk-benefit ratio. Deep learning (DL) models may be able to assist with this patient selection.
Pilot Projects Thrombolytic Therapy Stroke Brain Ischemia Humans Deep Learning
View on PubMed DOI

Computed Tomography-Based Radiomic Features Could Potentially Predict Microsatellite Instability Status in Stage II Colorectal Cancer: A Preliminary Study.

Academic radiology Mar 28, 2019
RATIONALE AND OBJECTIVES: To investigate whether quantitative radiomics features extracted from computed tomography (CT) can predict microsatellite instability (MSI) status in an Asian cohort of patients with stage Ⅱ colorectal cancer (CRC).
Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Humans Middle Aged ROC Curve Predictive Value of Tests Neoplasm Staging Adult Colorectal Neoplasms Male Microsatellite Instability
View on PubMed DOI

Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.

Academic radiology Jan 31, 2019
RATIONALE AND OBJECTIVES: Breast segmentation using the U-net architecture was implemented and tested in independent validation datasets to quantify fibroglandular tissue volume in breast MRI.
Female Young Adult Adult Breast Neoplasms Humans Neural Networks, Computer Algorithms Magnetic Resonance Imaging Breast Middle Aged Breast Density Disease Progression Deep Learning
View on PubMed DOI

Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology Jan 30, 2019
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.
Adenocarcinoma Support Vector Machine Magnetic Resonance Imaging Rectum Rectal Neoplasms Humans Neoplasm Metastasis Male Middle Aged ROC Curve Liver Neoplasms Algorithms Retrospective Studies Female
View on PubMed DOI

Machine Learning to Differentiate T2-Weighted Hyperintense Uterine Leiomyomas from Uterine Sarcomas by Utilizing Multiparametric Magnetic Resonance Quantitative Imaging Features.

Academic radiology Jan 17, 2019
RATIONALE AND OBJECTIVE: Uterine leiomyomas with high signal intensity on T2-weighted imaging (T2WI) can be difficult to distinguish from sarcomas. This study assessed the feasibility of using machine learning to differentiate uterine sarcomas from l...
Humans Diagnosis, Differential Uterus Female Sarcoma Machine Learning Aged Uterine Neoplasms Algorithms Adult Leiomyoma Retrospective Studies Middle Aged Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging
View on PubMed DOI

Detection of Extraprostatic Extension of Cancer on Biparametric MRI Combining Texture Analysis and Machine Learning: Preliminary Results.

Academic radiology Jan 14, 2019
RATIONALE AND OBJECTIVES: Extraprostatic extension of disease (EPE) has a major role in risk stratification of prostate cancer patients. Currently, pretreatment local staging is performed with MRI, while the gold standard is represented by histopatho...
Prostate Prostatectomy Risk Assessment Magnetic Resonance Imaging Neoplasm Invasiveness Predictive Value of Tests Bayes Theorem Prostatic Neoplasms Neoplasm Staging Prognosis Aged Male Middle Aged Humans Machine Learning Algorithms
View on PubMed DOI

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

Academic radiology Nov 23, 2018
RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential t...
Aged Predictive Value of Tests Humans Middle Aged Aged, 80 and over Tidal Volume Retrospective Studies Pulmonary Disease, Chronic Obstructive Airway Resistance Disease Progression Female Male Functional Residual Capacity Support Vector Machine
View on PubMed DOI
Popular Topics
Popular Journals