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Editorial: Introduction to the Issue on Domain Enriched Learning for Medical Imaging

Vishal Monga, Scott T. Acton, Abd-Krim Seghouane, Arrate Munoz-Barrutia, Jong Chul Ye
2020 IEEE Journal on Selected Topics in Signal Processing  
Subject-specific brain image priors are exploited for MR reconstruction in: "Enhanced Deep-learning-based Magnetic Resonance Image Reconstruction by Leveraging Prior Subjectspecific Brain Imaging: Proof-of-concept  ...  using a Cohort of Presumed Normal Subjects".  ... 
doi:10.1109/jstsp.2020.3021275 fatcat:v5tbzsx5rvbp7kcb67upumsskq

Proceedings of the World Molecular Imaging Congress 2021, October 5-8, 2021: General Abstracts

2022 Molecular Imaging and Biology  
An efficient rapidly converging deconvolution algorithm with a novel resolution subsets-based approach RSEMD for improving the quantitative accuracy of previously reconstructed clinical MRI images by commercial  ...  Results: In all of the phantom and patients' MRI studies the post-processed images proved to have higher resolution and contrast as compared with images reconstructed by conventional methods.  ...  Using serial image-based ROI data from 4-48h p.i., prospective Lu-177 dosimetry was estimated assuming complete local absorption of β particles only.  ... 
doi:10.1007/s11307-021-01693-y pmid:34982365 pmcid:PMC8725635 fatcat:4sfb3isoyfdhfbiwxfr55gvqym

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation [article]

Nima Tajbakhsh, Laura Jeyaseelan, Qian Li, Jeffrey Chiang, Zhihao Wu, Xiaowei Ding
2020 arXiv   pre-print
However, rarely do we have a perfect training dataset, particularly in the field of medical imaging, where data and annotations are both expensive to acquire.  ...  Recently, a large body of research has studied the problem of medical image segmentation with imperfect datasets, tackling two major dataset limitations: scarce annotations where only limited annotated  ...  Angermann et al. (2019) make use of intensity projections, specifically maximum intensity projections (MIP) at multiple angles, which are then fused to create a 2.5D representation of magnetic resonance  ... 
arXiv:1908.10454v2 fatcat:mjvfbhx75bdkbheysq3r7wmhdi

Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature [article]

Javier Juan-Albarracín
2020 arXiv   pre-print
The HTS builds on the concept of habitats. An habitat is defined as a sub-region of the lesion with a particular MRI profile describing a specific physiological behavior.  ...  This thesis focuses on the research and development of the Hemodynamic Tissue Signature (HTS) method: an unsupervised machine learning approach to describe the vascular heterogeneity of glioblastomas by  ...  Magnetic Resonance Imaging Magnetic Resonance Imaging (MRI) is a medical imaging technique used to provide invivo internal representations of the human body.  ... 
arXiv:2009.06288v1 fatcat:dum2y7fuuve73lxbb2any6iak4

ECR 2012 Book of Abstracts - A - Postergraduate Educational Programme

2012 Insights into Imaging  
Molecular imaging represents a group of integrated and complementary methods that evaluate the biological information resolved in time and space in vivo, at high resolution and by using with specific probes  ...  Beside abdominal plain film and ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) are two new and powerful imaging methods that have basically revolutionised the role  ...  The problem can be alleviated by using prior knowledge about the object to be reconstructed.  ... 
doi:10.1007/s13244-012-0153-4 pmid:22696127 pmcid:PMC3481066 fatcat:te6ctbtakzh5njsw43geghw3ta

ECR 2015 Book of Abstracts - A - Postgraduate Educational Programme

2015 Insights into Imaging  
The role of magnetic resonance imaging with specific sequences in this group of patients will be discussed.  ...  (DWI), dynamic contrast-enhanced MRI (DCE) and magnetic resonance spectroscopic imaging (MRSI).  ...  Functional magnetic resonance imaging (fMRI) is a noninvasive technique for measuring and mapping of brain activity.  ... 
doi:10.1007/s13244-015-0386-0 pmid:25708993 pmcid:PMC4349897 fatcat:m7eyvqcwojfpvf3lr5hy6dwjb4

ECR 2013 Book of Abstracts - A - Postgraduate Educational Programme

2013 Insights into Imaging  
The role of magnetic resonance imaging with specific sequences in this group of patients will be discussed.  ...  (DWI), dynamic contrast-enhanced MRI (DCE) and magnetic resonance spectroscopic imaging (MRSI).  ...  Functional magnetic resonance imaging (fMRI) is a noninvasive technique for measuring and mapping of brain activity.  ... 
doi:10.1007/s13244-013-0227-y pmid:23468009 pmcid:PMC3666656 fatcat:yitsk227mba2pl7wcypouf6tz4

ECR 2016 Book of Abstracts - A - Postgraduate Educational Programme

2016 Insights into Imaging  
The role of magnetic resonance imaging with specific sequences in this group of patients will be discussed.  ...  (DWI), dynamic contrast-enhanced MRI (DCE) and magnetic resonance spectroscopic imaging (MRSI).  ...  Functional magnetic resonance imaging (fMRI) is a noninvasive technique for measuring and mapping of brain activity.  ... 
doi:10.1007/s13244-016-0474-9 pmid:26873353 pmcid:PMC4762839 fatcat:itxslbcacjhh3kixfkcwmdbt44

ECR 2011 Book of Abstracts - A - Postgraduate Educational Programme

2011 Insights into Imaging  
The role of magnetic resonance imaging with specific sequences in this group of patients will be discussed.  ...  (DWI), dynamic contrast-enhanced MRI (DCE) and magnetic resonance spectroscopic imaging (MRSI).  ...  Functional magnetic resonance imaging (fMRI) is a noninvasive technique for measuring and mapping of brain activity.  ... 
doi:10.1007/s13244-011-0078-3 pmid:23100070 pmcid:PMC3533621 fatcat:qa3ln4hhvve2hhumgwwnmykgoe

The Proceedings of the 19th International Cancer Imaging Society Meeting and Annual Teaching Course

2019 Cancer Imaging  
However, in case of a cystic lesion, magnetic resonance imaging (MRI) is more appropriate.  ...  Conclusions We have proposed a robust, automatic, deep-learning-based delineation method on contrast-free MR sequence (T2W-FS) for NPC. 4 . 4 Prior F, Almeida J, Kathiravelu P, Kurc T, Smith K, Fitzgerald  ...  Therefore, we aimed to evaluate the accuracy of whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) for diagnosis, staging and follow-up of patients with a suspicion of gastric cancer  ... 
doi:10.1186/s40644-019-0244-2 fatcat:24addaecrngdvc2c6v37ai5qeq

PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRI [article]

Jingfen Xie, Jian Zhang, Yongbing Zhang, Xiangyang Ji
2022 arXiv   pre-print
Instead of learning a deterministic mask, the proposed sampling subnet explores an optimal probabilistic sub-sampling pattern, which describes independent Bernoulli random variables at each possible sampling  ...  Extensive experiments on two widely used MRI datasets demonstrate that our proposed PUERT not only achieves state-of-the-art results in terms of both quantitative metrics and visual quality but also yields  ...  leveraging prior subject-specific brain imaging: Proof-of-concept using SampNet and obtain performance improvements.  ... 
arXiv:2204.11189v1 fatcat:w47cgyn44ffojng3m6wlliamky

ECR 2011 Book of Abstracts - B - Scientific Sessions

2011 Insights into Imaging  
using Wilcoxon test.  ...  CT and, after 7-21 days, by MR imaging were retrospectively analysed.  ...  is presumed by mistake.  ... 
doi:10.1007/s13244-011-0077-4 pmid:23100071 pmcid:PMC3533624 fatcat:lytbu2vohbhhnorjqlpogl77iu

Full Issue PDF

2020 JACC Cardiovascular Imaging  
We then applied these conditions in a first-inhuman study to test the hypothesis that contrast US can increase limb perfusion in normal subjects and patients with peripheral artery disease (PAD).  ...  Microvascular perfusion was evaluated by US perfusion imaging, and in vivo adenosine triphosphate (ATP) release was assessed using in vivo optical imaging.  ...  CT-FFR values were computed using a recently introduced machine-learning algorithm (15). This approach is based on a deep learning framework to determine the functional severity of the lesion.  ... 
doi:10.1016/s1936-878x(20)30146-7 fatcat:4lngerhk4ngkfpdi6ddinbl4te

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Michael W. Weiner, Dallas P. Veitch, Paul S. Aisen, Laurel A. Beckett, Nigel J. Cairns, Jesse Cedarbaum, Robert C. Green, Danielle Harvey, Clifford R. Jack, William Jagust, Johan Luthman, John C. Morris (+7 others)
2015 Alzheimer's & Dementia  
The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal  ...  fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients.  ...  served on the scientific advisory boards for Lilly, Araclon and Institut Catala de Neurociencies Aplicades, Gulf War Veterans Illnesses Advisory Committee, VACO, Biogen Idec, and Pfizer; has served as a  ... 
doi:10.1016/j.jalz.2014.11.001 pmid:26073027 pmcid:PMC5469297 fatcat:2k7ag6astffy5gphqxf5lodkdq

Abstracts

2019 Stereotactic and Functional Neurosurgery  
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  ...  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  ...  Results: A total of over 100 subjects have been enrolled in this specific cohort.  ... 
doi:10.1159/000501568 fatcat:pv2k5hzuindpdmffhvqlkl25ji
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