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Published on Aug 14, 2018in Frontiers in Neuroinformatics 2.68
Diego Castillo-Barnes3
Estimated H-index: 3
,
Julia Ramírez35
Estimated H-index: 35
+ 3 AuthorsJuan Manuel Górriz33
Estimated H-index: 33
In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD) system for Parkinson's Disease (PD) have been proposed. Most of these methods have focused almost exclusively on brain images through the use of Machine-Learning algorithms suitable to characterize structural or functional patterns. Those patterns provide enough information about the status and/or the progression at intermediate and advanced stages of Parkinson's Disease. Nevertheless this information could ...
Published on Aug 1, 2018in Medical Image Analysis 8.88
Nicola Amoroso9
Estimated H-index: 9
(INFN: Istituto Nazionale di Fisica Nucleare),
Marianna La Rocca4
Estimated H-index: 4
(INFN: Istituto Nazionale di Fisica Nucleare)
+ 2 AuthorsSabina Tangaro13
Estimated H-index: 13
(INFN: Istituto Nazionale di Fisica Nucleare)
Abstract Parkinson’s disease (PD) is the most common neurological disorder, after Alzheimer’s disease, and is characterized by a long prodromal stage lasting up to 20 years. As age is a prominent factor risk for the disease, next years will see a continuous increment of PD patients, making urgent the development of efficient strategies for early diagnosis and treatments. We propose here a novel approach based on complex networks for accurate early diagnoses using magnetic resonance imaging (MRI)...
Published on Jul 26, 2018in Frontiers in Neurology 2.63
Qi Feng1
Estimated H-index: 1
(Bengbu Medical College),
Yuanjun Chen1
Estimated H-index: 1
+ 5 AuthorsZhongxiang Ding2
Estimated H-index: 2
Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disease causes the decline of some cognitive impairments. The present study aimed to identify the corpus callosum (CC) radiomic features related to the diagnosis of AD and build and evaluate a classification model. Methods: Radiomics analysis was applied to the three-dimensional T1-weighted magnetization-prepared rapid gradient echo (MPRAGE) images of 78 patients with AD and 44 healthy controls (HC). The CC, in each subject,...
Published on Jun 1, 2018
Nazrul Hoque7
Estimated H-index: 7
(Kaziranga University),
Mihir Singh1
Estimated H-index: 1
(Tezpur University),
Dhruba Kumar Bhattacharyya23
Estimated H-index: 23
(Tezpur University)
Feature selection methods have been used in various applications of machine learning, bioinformatics, pattern recognition and network traffic analysis. In high dimensional datasets, due to redundant features and curse of dimensionality, a learning method takes significant amount of time and performance of the model decreases. To overcome these problems, we use feature selection technique to select a subset of relevant and non-redundant features. But, most feature selection methods are unstable i...
Published on Feb 1, 2018in European Radiology 3.96
Albert Stezin3
Estimated H-index: 3
(National Institute of Mental Health and Neurosciences),
Rajini M. Naduthota3
Estimated H-index: 3
(National Institute of Mental Health and Neurosciences)
+ 5 AuthorsPramod Kumar Pal25
Estimated H-index: 25
(National Institute of Mental Health and Neurosciences)
Objective To determine the diagnostic characteristics of poor visualisation of nigrosome-1 as a neuroimaging biomarker in Parkinson’s disease (PD) and to explore the relationship of poor visualisation of nigrosome-1 and clinical asymmetry.
Published on Jan 1, 2018in Human Brain Mapping 4.55
Young Hee Sung6
Estimated H-index: 6
(Gachon University),
Jongho Lee18
Estimated H-index: 18
(SNU: Seoul National University)
+ 4 AuthorsEung Yeop Kim26
Estimated H-index: 26
(Gachon University)
In this study, the prevalence of abnormality in putative nigrosome 1 and nigrosome 4 (N1 and N4, respectively) was investigated in early versus late-stage idiopathic Parkinson's disease (IPD) patients. A total of 128 IPD patients (early stage[n = 89]; late stage[n = 39]) and 15 healthy subjects were scanned for high-resolution (0.5 × 0.5 × 1.0 mm3) multiecho gradient-recalled echo MRI and dopamine transporter PET imaging. The MRI data were processed for susceptibility map-weighted imaging (SMWI)...
Published on Jan 1, 2018in Journal of Clinical Neurology 2.80
Eung Yeop Kim26
Estimated H-index: 26
(Gachon University),
Young Hee Sung6
Estimated H-index: 6
(Gachon University)
+ 3 AuthorsJongho Lee18
Estimated H-index: 18
(SNU: Seoul National University)
Published on Dec 1, 2017in BMC Neurology 2.23
Manuel A. Schmidt4
Estimated H-index: 4
,
Tobias Engelhorn34
Estimated H-index: 34
+ 5 AuthorsArnd Doerfler51
Estimated H-index: 51
The loss of the swallow-tail sign of the substantia nigra has been proposed for diagnosis of Parkinson’s disease. Aim was to evaluate, if the sign occurs consistently in healthy subjects and if it can be reliably detected with high-resolution 7T susceptibility weighted imaging (SWI). Thirteen healthy adults received SWI at 7T. 3 neuroradiologists, who were blinded to patients’ diagnosis, independently classified subjects regarding the swallow-tail sign to be present or absent. Accuracy, positive...
Published on Nov 1, 2017in Cancer Research 8.38
Joost J.M. van Griethuysen3
Estimated H-index: 3
(UM: Maastricht University),
Andriy Fedorov18
Estimated H-index: 18
(Brigham and Women's Hospital)
+ 7 AuthorsHugo J.W.L. Aerts38
Estimated H-index: 38
(Brigham and Women's Hospital)
Radiomics aims to quantify phenotypic characteristics on medical imaging through the use of automated algorithms. Radiomic artificial intelligence (AI) technology, either based on engineered hard-coded algorithms or deep learning methods, can be used to develop noninvasive imaging-based biomarkers. However, lack of standardized algorithm definitions and image processing severely hampers reproducibility and comparability of results. To address this issue, we developed PyRadiomics , a flexible ope...
Published on Aug 1, 2017in Clinical Cancer Research 8.91
Bin Zhang6
Estimated H-index: 6
(Southern Medical University),
Jie Tian53
Estimated H-index: 53
(CAS: Chinese Academy of Sciences)
+ 15 AuthorsShufang Pei2
Estimated H-index: 2
(Southern Medical University)
Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC). Experimental Design: One-hundred and eighteen patients (training cohort: n = 88; validation cohort: n = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-fre...
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