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q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans
[chapter]
2015
Lecture Notes in Computer Science
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This method allows obtaining scalar measures from advanced models at twelve-fold reduced scan time and detecting abnormalities without using diffusion models. ...
We demonstrate how deep learning, a group of algorithms in the field of artificial neural networks, can be applied to reduce diffusion MRI data processing to a single optimized step. ...
Pölsterl and B. Menze (TU München) for discussions. V. Golkov is supported by the Deutsche Telekom Foundation. ...
doi:10.1007/978-3-319-24553-9_5
fatcat:q6k5nzqnkrgptge3dykmg72mfe
Deep Learning Based Pain Treatment
2019
International Journal of Trend in Scientific Research and Development
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Among machine learning methods, a subset has so far been applied to pain research-related problems, SVMs, regression models, deep learning and several kinds of neural networks so far most often revealed ...
Therefore, machine learning has the capability to encouragement the training and dealing of pain greatly. ...
This modification allows obtaining scalar measures from advanced models at twelve-fold reduced scan time and detecting abnormalities without using diffusion models. ...
doi:10.31142/ijtsrd23639
fatcat:tqg4u3tkgjhmjpya67g3lnewwu
The Learning Curve for Surgical Resection of Vestibular Schwannoma
2012
Journal of Neurological Surgery. Part B: Skull Base: an interdisciplinary approach
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The minimally invasive access through an eyelid incision involves dissection in normal tissue planes, preserves frontalis muscle fi bers, avoids injury to the fronto-temporal facial nerve branches, and ...
cient (ADC) maps for diffusion-weighted imaging. ...
Radiological diagnosis rested on the use of brain MRI, MRA, MRV, and thin slice CT scan of petrous bone and clivus. ...
doi:10.1055/s-0032-1312151
fatcat:qfsmiu5eejdhfbq4e2kwdcttju
Learning Capacity in Simulated Virtual Neurological Procedures
2020
Journal of WSCG
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ACKNOWLEDGMENTS The authors acknowledge the support of the NSERC/Creaform Industrial Research Chair on 3-D Scanning for conducting the work presented in this paper. ...
ACKNOWLEDGEMENTS The authors would like to thank Oana Rotaru-Orhei for her comments and the three anonymous reviewers for their insightful suggestions. ...
., and Bronstein, M., Geometric
deep learning on graphs and manifolds using mix-
ture model CNNs, in Conf. Proc. CVPR'17, 2017. ...
doi:10.24132/csrn.2020.3001.13
fatcat:uytlm7nytrhmnk553ellfhl54a
Effects of errorless learning on the acquisition of velopharyngeal movement control
2012
Journal of the Acoustical Society of America
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The SIR provides a local description of the reverberant field of that environment as a function of both time and space. ...
Computational skills allow rapid and automatic "statistical learning" and social interaction is necessary for this computational learning process to occur. ...
pathways (raster scanning, spiral scanning from the center to the outside and from the outside to the center), spot spacing, and motion time. ...
doi:10.1121/1.4708235
fatcat:7wzupz5u2nd6nc7ttvbpxwvunm
2014 Biennial Meeting of the American Society for Stereotactic and Functional Neurosurgery. Washington, D.C., USA, May 31-June 3, 2014: Abstracts
2014
Stereotactic and Functional Neurosurgery
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with the MRI scan. ...
A volumetric CT scan was obtained post implantation and also registered to the planning MRI scan to measure deviations from the plan. ...
doi:10.1159/000363530
pmid:24902536
fatcat:f3ptvsfgnfat7osvq5gugpk4gq
CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020
2020
International Journal of Computer Assisted Radiology and Surgery
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A hybrid (analogue and digital) CARS 2020 has therefore been envisaged to take place at the University Hospital in Munich, with a balanced combination of analogue/personal and digital presentations and ...
Preface Analogue and Digital CARS 2020 Congress The overarching purpose of the scholarly publication and communication process of IJCARS in the context of the CARS congress could be defined as: "To enable ...
In order to reduce the radiation exposure, a 4 DOF robot system that controls the guidewire and the catheter and offers haptic feedback function for the guidewire insertion has been developed by Cha et ...
doi:10.1007/s11548-020-02171-6
pmid:32514840
fatcat:lyhdb2zfpjcqbf4mmbunddwroq
20th IPA International Congress 2–3 October 2020 Virtual Learning
2020
International Psychogeriatrics
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The Mass Observation Project, established in 1937, documents the lives of ordinary people living in the UK, and explores a wide range of health and social issues. ...
This symposium brings together insights from a wide range of disciplines to explore the utility of Mass Observation Data (http://www.massobs.org.uk/) in the field of gerontology and mental health. ...
RESULTS: In our pilot work, we predicted a person's age from their MRI scan with a mean absolute error of about 5 years. ...
doi:10.1017/s1041610220002525
fatcat:q4yez2ziirfvtkws7rofmottq4
2006 Biennial Meeting of the American Society for Stereotactic and Functional Neurosurgery. Boston, Mass., June 1–4, 2006
2006
Stereotactic and Functional Neurosurgery
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Parametric analysis of learning was estimated by using the state-space model, and the rate of learning (SI) calculated by fitting the learning curves to a logistic equation. ...
Ten patients were treated with MRI scan guided stereotactic frame based surgical resection. Twelve patients were treated with MRI-scan guided frameless neuronavigation systems. ...
Several bioelectrical models have been made, but they are of limited value, due to the complexity of modeling accurately the electrode and components of brain tissue. ...
doi:10.1159/000097756
fatcat:g4hd2dulcbf5pgylow74icmsxy
Proceedings of the World Molecular Imaging Congress 2021, October 5-8, 2021: General Abstracts
2022
Molecular Imaging and Biology
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The uncertainty caused in the system was modeled as an iterative deconvolution with resolution subsets to denoise and enhance image resolution. ...
Materials and Methods: The method was tested on ACR MRI phantom and DICOM clinical MRI data. Data acquisition was performed on a commercial Siemens MRI system. ...
., the corresponding tumor-to-organ activity ratios (T:NT) for blood, non-tumored liver and kidney were respectively 17. 6 ± 6.3, 19.4 ± 5.3, and 6.3 ± 1.3, and at 48h p.i. ...
doi:10.1007/s11307-021-01693-y
pmid:34982365
pmcid:PMC8725635
fatcat:4sfb3isoyfdhfbiwxfr55gvqym
MRI-Guided Focused Ultrasound Surgery
2009
Annual Review of Medicine
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Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequence of their ...
Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. ...
Support by the Conseil Régional d'Aquitaine, Ligue National Contre le Cancer, Imagerie du Petit Animal and Philips Medical Systems is gratefully acknowledged. ...
doi:10.1146/annurev.med.60.041707.170303
pmid:19630579
pmcid:PMC4005559
fatcat:7ojh6xtfc5ckvloxhnfb5dxtmi
Developing Techniques for Quantitative Renal Magnetic Resonance Imaging
2021
Zenodo
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This is done without the need for ionising radiation and often without exogenous contrast agents, thus making MRI an ideal tool for both clinical and research use. ...
The kidneys are morphologically and functionally complex organs and as such, lend themselves to complex methodologies of study. One such methodology is quantitative Magnetic Resonance Imaging (MRI). ...
Deep learning is a class of machine learning algorithms that can model high-level information in an image using several processing layers of transformations. ...
doi:10.5281/zenodo.5524888
fatcat:ba4f7zyabfckjlbtdyi6p5u3oy
SPR 2020
2020
Pediatric Radiology
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Conclusions: We successfully applied deep learning networks trained on unstructured free-text; our methodology exhibited high accuracy and ROC-AUC for abuse classification. ...
The best deep learning model (ResNet) achieved sensitivity, specificity, and AUC (area under the curve) of 0.90 (0.01), 0.82 (0.03) and 0.86 (0.02), respectively on the test set. ...
A Comparison of Radiograph and MRI Predictive Value Haitham Awdeh, Haitham.K.Awdeh@uth.tmc.edu; Andrew J. Bosserman, Michael Q. ...
doi:10.1007/s00247-020-04679-0
pmid:32435980
fatcat:y6da6d4blvaxlkus6w6zahpwlu
ECR 2011 Book of Abstracts - B - Scientific Sessions
2011
Insights into Imaging
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Methods and Materials: Thirty-one biopsy-proven HCCs (diameter, 1-3 cm) in 18 consecutive cirrhotic patients (12 males and 6 females; age: 50±13 years) scanned by multiphase contrast-enhanced 64-row multidetector ...
and hypervascular on MR. ...
B-387 11:24 Quantification of liver fibrosis using diffusion-weighted MR imaging and proton MR spectroscopy in experimental rabbit models Q. Wang, C. Liang, H. ...
doi:10.1007/s13244-011-0077-4
pmid:23100071
pmcid:PMC3533624
fatcat:lytbu2vohbhhnorjqlpogl77iu
Abstracts
2019
Stereotactic and Functional Neurosurgery
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Objectives: This was an open-label, phase I clinical trial to evaluate efficacy and safety of bilateral caudate nucleus neuromodulation by deep brain stimulation (DBS) for adults with chronic tinnitus ...
The purpose of this study is to evaluate the safety of the MR guided focused ultrasound (MRgFUS) using ExAblate ® Model 4000 Type 2.0 used as a tool to disrupt the blood brain barrier (BBBD) in patients ...
Pre-op MRI scans and post-op CT scans were co-registered and normalized to MNI space. The volume of activated tissue (VAT) was generated for each electrode contact at different voltages (1V to 5V). ...
doi:10.1159/000501568
fatcat:pv2k5hzuindpdmffhvqlkl25ji
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