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Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer's Disease [chapter]

Pierrick Coupé, Simon F. Eskildsen, José V. Manjón, Vladimir Fonov, D. Louis Collins
2011 Lecture Notes in Computer Science  
Conclusion: Using the volume and the grade of the HC at the same time resulted in an efficient patient classification with a success rate of 90%.  ...  Results: First, the evaluation of HC segmentation accuracy yielded a Dice's Kappa of 0.88 for CN and 0.84 for AD. Second, the proposed HC grading enables detection of AD with a success rate of 89%.  ...  Alzheimer's disease (AD) [1] .  ... 
doi:10.1007/978-3-642-23626-6_19 fatcat:pqfd5le6zbepvls4wombyekhda

Differential diagnosis of neurodegenerative diseases using structural MRI data

Juha Koikkalainen, Hanneke Rhodius-Meester, Antti Tolonen, Frederik Barkhof, Betty Tijms, Afina W. Lemstra, Tong Tong, Ricardo Guerrero, Andreas Schuh, Christian Ledig, Daniel Rueckert, Hilkka Soininen (+6 others)
2016 NeuroImage: Clinical  
This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia.  ...  The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge.  ...  Patients were diagnosed with probable AD using the criteria of the National Institute for Neurological and Communicative Diseases Alzheimer's Disease and Related Disorders Association; all patients also  ... 
doi:10.1016/j.nicl.2016.02.019 pmid:27104138 pmcid:PMC4827727 fatcat:kaz3wh4vxjgmbm3ys2umpimtaa

A Large-scale Comparison of Cortical and Subcortical Structural Segmentation Methods in Alzheimer's Disease: a Statistical Approach [article]

Jafar Zamani, Ali Sadr, Amir-Homayoun Javadi
2020 bioRxiv   pre-print
HIPS, volBrain, CAT and BrainSuite segmentation methods were used for the subfields of hippocampus, and the rest of the brain.  ...  Our results showed that automated segmentation methods HIPS, volBrain and CAT can be used in the classification of AD and HC.  ...  Simultaneous segmentation and grading of anatomical structures for patient's classification: Application to Alzheimer's disease. NeuroImage 59, 3736-3747 (2012). 134. Sperling, R. A. et al.  ... 
doi:10.1101/2020.08.18.256321 fatcat:ph657ht2pffjbnx3g46xxzvi7i

Simultaneous segmentation and grading of anatomical structures for patient's classification: Application to Alzheimer's disease

Pierrick Coupé, Simon F. Eskildsen, José V. Manjón, Vladimir S. Fonov, D. Louis Collins
2012 NeuroImage  
The proposed method simultaneously performs segmentation and grading of structures to efficiently capture the anatomical alterations caused by AD.  ...  In this paper, we propose an innovative approach to robustly and accurately detect Alzheimer's disease (AD) based on the distinction of specific atrophic patterns of anatomical structures such as hippocampus  ...  This work benefited from the use of ITK-SNAP from the Insight Segmentation and Registration Toolkit (ITK) for 3D rendering.  ... 
doi:10.1016/j.neuroimage.2011.10.080 pmid:22094645 fatcat:htbvafrvo5a7ncypife2m6xram

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting

Tong Tong, Christian Ledig, Ricardo Guerrero, Andreas Schuh, Juha Koikkalainen, Antti Tolonen, Hanneke Rhodius, Frederik Barkhof, Betty Tijms, Afina W Lemstra, Hilkka Soininen, Anne M Remes (+7 others)
2017 NeuroImage: Clinical  
in Neurodegenerative Diseases).  ...  Acknowledgements This work was funded under the Seventh Framework Programme by the European Commission (http://cordis.europa.eu; EU-Grant-611005-PredictND; Name: From Patient Data to Clinical Diagnosis  ...  Association (McKhann et al., 2011) and the criteria of National Institute for Neurological and Communicative Diseases Alzheimer's Disease and Related Disorders Association (McKhann et al., 1984) ;  ... 
doi:10.1016/j.nicl.2017.06.012 pmid:28664032 pmcid:PMC5479966 fatcat:rlbcoofhfjcfndgkf33lthvnci

Detection of Alzheimer's disease signature in MR images seven years before conversion to dementia: Toward an early individual prognosis

Pierrick Coupé, Vladimir S. Fonov, Charlotte Bernard, Azar Zandifar, Simon F. Eskildsen, Catherine Helmer, José V. Manjón, Hélène Amieva, Jean-François Dartigues, Michèle Allard, Gwenaelle Catheline, D. Louis Collins
2015 Human Brain Mapping  
subjects and patients with AD.  ...  Finding very early biomarkers of Alzheimer's Disease (AD) to aid in individual prognosis is of major interest to accelerate the development of new therapies.  ...  Collins is a consultant for NeuroRx Inc. and co-founder of True Positive Medical Devices Inc.  ... 
doi:10.1002/hbm.22926 pmid:26454259 fatcat:spmhzi6lvnd5vkzhprgdgnwugm

Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting

Dan Wu, Can Ceritoglu, Michael I. Miller, Susumu Mori
2016 NeuroImage: Clinical  
We tested this concept first by estimating age in a normal population; we then performed functional and diagnostic estimations in Alzheimer's disease patients.  ...  In this study, we extended the role of the atlas library from mere anatomical reference to a comprehensive knowledge database with various patient attributes, such as demographic, functional, and diagnostic  ...  This arrangement is being managed by the Johns Hopkins University in accordance with its conflict of interest policies.  ... 
doi:10.1016/j.nicl.2016.09.008 pmid:27689021 pmcid:PMC5031476 fatcat:gwtpgoopwbhalgspiildczb7ca

Adaptive fusion of texture-based grading for Alzheimer's disease classification

Kilian Hett, Vinh-Thong TA, José V. Manjón, Pierrick Coupé
2018 Computerized Medical Imaging and Graphics  
Adaptive fusion of texture-based grading for Alzheimer's disease classification. Computerized Medical Imaging and Graphics.  ...  Moreover, our method obtains competitive performance with 91.3% of accuracy and 94.6% of area under a curve for AD detection.  ...  The obtained hippocampus were segmented according to the EADC protocol [5] designed for AD studies.  ... 
doi:10.1016/j.compmedimag.2018.08.002 pmid:30273832 fatcat:estoaoliuzeflebvdy22nuvc7a

Evaluating combinations of diagnostic tests to discriminate different dementia types

Marie Bruun, Hanneke F.M. Rhodius-Meester, Juha Koikkalainen, Marta Baroni, Le Gjerum, Afina W. Lemstra, Frederik Barkhof, Anne M. Remes, Timo Urhemaa, Antti Tolonen, Daniel Rueckert, Mark van Gils (+8 others)
2018 Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring  
Methods: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls.  ...  Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal  ...  The classification for "grading" consists of eight grading features and "vascular burden" consists of three features: volume of WMHs, volume of cortical infarcts, and volume of lacunar infarcts.  ... 
doi:10.1016/j.dadm.2018.07.003 pmid:30320203 pmcid:PMC6180596 fatcat:qnnijbytlrggnpm6iqxg5rlxs4

Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database

Rémi Cuingnet, Emilie Gerardin, Jérôme Tessieras, Guillaume Auzias, Stéphane Lehéricy, Marie-Odile Habert, Marie Chupin, Habib Benali, Olivier Colliot
2011 NeuroImage  
Recently, several high dimensional classification methods have been proposed to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly  ...  DARTEL significantly improved six out of 20 classification experiments and led to lower results in only two cases.  ...  Acknowledgments Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI; Principal Investigator: Michael Weiner; NIH grant U01 AG024904).  ... 
doi:10.1016/j.neuroimage.2010.06.013 pmid:20542124 fatcat:to7wumexjngmdayuswfkn7dyu4

A list of publications describing new supervised learning pipelines to predict clinical variables from neuroimaging data in Alzheimer's disease

Alex F Mendelson
2016 Figshare  
This is a list of publications describing new classification and regression methods to predict clinical variables relevant to Alzheimer's disease using neurological images.  ...  It is intended as a companion document for my thesis.  ...  Simultaneous segmentation and grading of hippocampus for patient classification with Alzheimer's disease. In Medical Image Computing and Computer-Assisted Intervention-MICCAI 2011, pages 149-157.  ... 
doi:10.6084/m9.figshare.3435752 fatcat:mdtfbkinjzfezcg6qhhwx43s4e

Automatic Prediction of Cognitive and Functional Decline Can Significantly Decrease the Number of Subjects Required for Clinical Trials in Early Alzheimer's Disease

Neda Shafiee, Mahsa Dadar, Simon Ducharme, D. Louis Collins, the Alzheimer's Disease Neuroimaging Initiative for
2021 Journal of Alzheimer's Disease  
early Alzheimer's disease.  ...  While both cognitive and magnetic resonance imaging (MRI) data has been used to predict progression in Alzheimer's disease, heterogeneity between patients makes it challenging to predict the rate of cognitive  ...  Neurology 49, 786-794. [12] Coupé P, Eskildsen SF, Manjón JV, Fonov VS, Collins DL 543 (2012) Simultaneous segmentation and grading of anatomical structures for patient's classification: Application to  ... 
doi:10.3233/jad-210664 pmid:34602478 pmcid:PMC8673508 fatcat:i6qswst6azftvj3jcibrnl7r4q

Structural imaging biomarkers of Alzheimer's disease: predicting disease progression

Simon F. Eskildsen, Pierrick Coupé, Vladimir S. Fonov, Jens C. Pruessner, D. Louis Collins
2015 Neurobiology of Aging  
Optimized MRI-based biomarkers of Alzheimer's disease (AD) may allow earlier detection and refined prediction of the disease.  ...  These features are the left and right hippocampus grading and cortical thicknesses of the left precuneus, left superior temporal sulcus, and right anterior part of the parahippocampal gyrus.  ...  Data collection and sharing for this project were funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904).  ... 
doi:10.1016/j.neurobiolaging.2014.04.034 pmid:25260851 fatcat:2xyeb5lo2fhcpgz7inbhljhc7e

Multimorbidity Is Associated with Preclinical Alzheimer's Disease Neuroimaging Biomarkers

Aline Mendes, Sophie Tezenas du Montcel, Marcel Levy, Anne Bertrand, Marie-Odile Habert, Hugo Bertin, Bruno Dubois, Stéphane Epelbaum
2018 Dementia and Geriatric Cognitive Disorders  
A practical 378 method for grading the cognitive state of patients for the clinician. J. 379 Psychiatr. Res. 1975;12:189-198. 380 9. Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL.  ...  Fully automatic hippocampus segmentation and classification in 385 Figure 1 . 1 Association association remains statistically significant after exclusion of this outlier 509 participant from the analysis  ... 
doi:10.1159/000489007 pmid:29953971 fatcat:yh3h5xjhrfa6faexsa3tii4zd4

IEEE Access Special Section Editorial: Deep Learning for Computer-Aided Medical Diagnosis

Yu-Dong Zhang, Zhengchao Dong, Shui-Hua Wang, Carlo Cattani
2020 IEEE Access  
In the article, ''Transfer learning with intelligent training data selection for prediction of Alzheimer's disease,'' by Khan et al. the researchers attempted to solve AD detection with transfer learning  ...  The datasets included 233 and 73 patients with a total of 3064 and 516 images on T1-weighted contrast-enhanced images for the first and second datasets, respectively.  ... 
doi:10.1109/access.2020.2996690 fatcat:m6r36o6udrbfrnvwsca2uzu5dm
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