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Novel economical, accurate, sensitive, single-cell analytical method for mitochondrial DNA quantification in mtDNA mutation carriers
PurposeAlthough a variety of analytical methods have been developed to detect mitochondrial DNA (mtDNA) heteroplasmy, there are special requirements...
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Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline
ObjectivesThis study aims at a fully automatic pipeline for measuring the magnetic resonance parkinsonism index (MRPI) using deep learning methods.
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Accurate 24-h urine cystine quantification for patients on cystine-binding thiol drugs
Cystinuria is a rare disorder resulting in development of recurrent kidney stones, adversely affecting patient quality of life. The goal of...
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Towards accurate 177Lu SPECT activity quantification and standardization using lesion-to-background voxel ratio
BackgroundConventional calibration of the gamma camera consists of the calculation of calibration factors (CFs) (ratio of counts/cc and true...
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Accurate quantification of 3′-terminal 2′-O-methylated small RNAs by utilizing oxidative deep sequencing and stem-loop RT-qPCR
The continuing discoveries of novel classes of RNA modifications in various organisms have raised the need for improving sensitive, convenient, and...
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Quantification and dosimetry of small volumes including associated uncertainty estimation
BackgroundAccurate quantification of radioactivity in a source of interest relies on accurate registration between SPECT and anatomical images, and...
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Validation of cardiac image-derived input functions for functional PET quantification
PurposeFunctional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate...
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Novel contouring method for optimizing MRI flow quantification in patients with aortic valve disease
Optimizing MRI aortic flow quantification is crucial for accurate assessment of valvular disease severity. In this study, we sought to evaluate the...
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Clinical validation of an AI-based automatic quantification tool for lung lobes in SPECT/CT
BackgroundLung lobar ventilation and perfusion (V/Q) quantification is generally obtained by generating planar scintigraphy images and then imposing...
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A deep learning model enables accurate prediction and quantification of pulmonary edema from chest X-rays
BackgroundA quantitative assessment of pulmonary edema is important because the clinical severity can range from mild impairment to life threatening....
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Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning
BackgroundRadiotherapy is a core treatment modality for oropharyngeal cancer (OPC), where the primary gross tumor volume (GTVp) is manually segmented...
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Blood loss quantification during major abdominal surgery: prospective observational cohort study
BackgroundBlood loss during major abdominal surgery is an essential parameter in the evaluation of strategies aimed at reducing perioperative...
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Automatic Segmentation of the Fetus in 3D Magnetic Resonance Images Using Deep Learning: Accurate and Fast Fetal Volume Quantification for Clinical Use
Magnetic resonance imaging (MRI) provides images for estimating fetal volume and weight, but manual delineations are time consuming. The aims were to...
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Abdominal fat quantification using convolutional networks
ObjectivesTo present software for automated adipose tissue quantification of abdominal magnetic resonance imaging (MRI) data using fully...
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Impact of reconstruction parameters on the accuracy of myocardial extracellular volume quantification on a first-generation, photon-counting detector CT
BackgroundThe potential role of cardiac computed tomography (CT) has increasingly been demonstrated for the assessment of diffuse myocardial fibrosis...
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Unsupervised domain adaptive tumor region recognition for Ki67 automated assisted quantification
PurposeKi67 is a protein associated with tumor proliferation and metastasis in breast cancer and acts as an essential prognostic factor. Clinical...
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Coronary artery calcium quantification technique using dual energy material decomposition: a simulation study
Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having...
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Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI
ObjectivesTime-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation...
