AIMC Topic: Magnetic Resonance Imaging
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[Deep learning for detection of radiographic sacroiliitis].
Zeitschrift fur Rheumatologie
Jun 23, 2021
DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution.
IEEE transactions on cybernetics
Jun 23, 2021
Thin-section magnetic resonance imaging (MRI) can provide higher resolution anatomical structures and more precise clinical information than thick-section images. However, thin-section MRI is not always available due to the imaging cost issue. In mul...
Behavioral correlates of cortical semantic representations modeled by word vectors.
PLoS computational biology
Jun 23, 2021
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...
Characterizing the Clinical Features and Atrophy Patterns of -Related Frontotemporal Dementia With Disease Progression Modeling.
Neurology
Jun 22, 2021
BACKGROUND AND OBJECTIVE: Mutations in the gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signature of mutations have grouped all different mutations together and shown an association with focal at...
Detecting neonatal acute bilirubin encephalopathy based on T1-weighted MRI images and learning-based approaches.
BMC medical imaging
Jun 22, 2021
BACKGROUND: Neonatal hyperbilirubinemia is a common clinical condition that requires medical attention in newborns, which may develop into acute bilirubin encephalopathy with a significant risk of long-term neurological deficits. The current clinical...
Robot assisted laser-interstitial thermal therapy with iSYS1 and Visualase: how I do it.
Acta neurochirurgica
Jun 19, 2021
BACKGROUND: Laser-interstitial thermal therapy (LITT) is an ablative treatment based on a surgically implanted laser-emitting catheter to induce a focal ablation of the pathological tissue. The main indications in neurosurgery are primary brain tumor...
Autoencoder based self-supervised test-time adaptation for medical image analysis.
Medical image analysis
Jun 19, 2021
Deep neural networks have been successfully applied to medical image analysis tasks like segmentation and synthesis. However, even if a network is trained on a large dataset from the source domain, its performance on unseen test domains is not guaran...
A review of medical image data augmentation techniques for deep learning applications.
Journal of medical imaging and radiation oncology
Jun 19, 2021
Research in artificial intelligence for radiology and radiotherapy has recently become increasingly reliant on the use of deep learning-based algorithms. While the performance of the models which these algorithms produce can significantly outperform ...
A Pupil Segmentation Algorithm Based on Fuzzy Clustering of Distributed Information.
Sensors (Basel, Switzerland)
Jun 19, 2021
Pupil segmentation is critical for line-of-sight estimation based on the pupil center method. Due to noise and individual differences in human eyes, the quality of eye images often varies, making pupil segmentation difficult. In this paper, we propos...
A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI.
Clinical imaging
Jun 18, 2021
PURPOSE: To investigate the diagnostic performance of a deep convolutional neural network for differentiation of clear cell renal cell carcinoma (ccRCC) from renal oncocytoma.
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