AIMC Topic: Quality Control
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Deep learning for patient-specific quality assurance: Identifying errors in radiotherapy delivery by radiomic analysis of gamma images with convolutional neural networks.
Medical physics
Dec 28, 2018
PURPOSE: Patient-specific quality assurance (QA) for intensity-modulated radiation therapy (IMRT) is a ubiquitous clinical procedure, but conventional methods have often been criticized as being insensitive to errors or less effective than other comm...
Multi-Institutional Validation of a Knowledge-Based Planning Model for Patients Enrolled in RTOG 0617: Implications for Plan Quality Controls in Cooperative Group Trials.
Practical radiation oncology
Dec 15, 2018
PURPOSE: This study aimed to evaluate the feasibility of using a single-institution, knowledge-based planning (KBP) model as a dosimetric plan quality control (QC) for multi-institutional clinical trials. The efficacy of this QC tool was retrospectiv...
Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.
The lancet. Gastroenterology & hepatology
Dec 6, 2018
Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance. Pooled miss rates for polyps are as high as 22%, and associated interval colorectal cancers after colonoscopy are of concern. Optical biopsy, whereby...
Soybean inoculants in Brazil: an overview of quality control.
Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
Nov 29, 2018
The bacterial strains SEMIA 587 and 5019 (Bradyrhizobium elkanii), 5079 (Bradyrhizobium japonicum), and 5080 (Bradyrhizobium diazoefficiens) are recommended for soybean inoculants in Brazil. In several countries, the current regulations are insuffici...
High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains.
Medical physics
Nov 28, 2018
PURPOSE: Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventional CT. In general, iterative reconstruction techniques have been applied to sparsely sampled CT to re...
Supervised machine learning quality control for magnetic resonance artifacts in neonatal data sets.
Human brain mapping
Nov 22, 2018
Quality control (QC) of brain magnetic resonance images (MRI) is an important process requiring a significant amount of manual inspection. Major artifacts, such as severe subject motion, are easy to identify to naïve observers but lack automated iden...
Learning-Based Quality Control for Cardiac MR Images.
IEEE transactions on medical imaging
Nov 1, 2018
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artifacts, such as cardiac...
New discretization method applied to NBV problem: Semioctree.
PloS one
Nov 1, 2018
This paper presents a discretization methodology applied to the NBV (Next Best View) problem, which consists of determining the heuristical best position of the next scan. This new methodology is a hybrid process between a homogenous voxelization and...
Framing the challenges of artificial intelligence in medicine.
BMJ quality & safety
Oct 5, 2018
A robotic system to prepare IV solutions.
International journal of medical informatics
Sep 11, 2018
Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly, negativities that threaten human health and life can be avoided, but they can cause unwanted situations that can occur until the end of life wh...
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