Visual-Saliency-Based Abnormality Detection for MRI Brain Images—Alzheimer’s Disease Analysis
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Visual-Saliency-Based Abnormality Detection for MRI Brain Images—Alzheimer’s Disease Analysis
Authors
Keywords
-
Journal
Applied Sciences-Basel
Volume 11, Issue 19, Pages 9199
Publisher
MDPI AG
Online
2021-10-04
DOI
10.3390/app11199199
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Identification of Alzheimer's Disease Based on Wavelet Transformation Energy Feature of the Structural MRI Image and NN Classifier
- (2020) Jinwang Feng et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- Multiple-kernel learning for genomic data mining and prediction
- (2019) Christopher M. Wilson et al. BMC BIOINFORMATICS
- Identification of the Early Stage of Alzheimer's Disease Using Structural MRI and Resting-State fMRI
- (2019) Seyed Hani Hojjati et al. Frontiers in Neurology
- Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease
- (2018) Diana L. Giraldo et al. Brain and Behavior
- Structural and functional brain scans from the cross-sectional Southwest University adult lifespan dataset
- (2018) Dongtao Wei et al. Scientific Data
- Alzheimer's Disease Detection Using Extreme Learning Machine, Complex Dual Tree Wavelet Principal Coefficients and Linear Discriminant Analysis
- (2018) Debesh Jha et al. Journal of Medical Imaging and Health Informatics
- Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks
- (2018) Silvia Basaia et al. NeuroImage-Clinical
- A hybrid feature extraction approach for brain MRI classification based on Bag-of-words
- (2018) Wadhah Ayadi et al. Biomedical Signal Processing and Control
- Multivariate Approach for Alzheimer’s Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization
- (2017) Yudong Zhang et al. JOURNAL OF ALZHEIMERS DISEASE
- A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
- (2017) Saima Rathore et al. NEUROIMAGE
- Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error
- (2016) Iman Beheshti et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Time-Varying Brain Connectivity in fMRI Data: Whole-brain data-driven approaches for capturing and characterizing dynamic states
- (2016) Vince D. Calhoun et al. IEEE SIGNAL PROCESSING MAGAZINE
- Selected Saliency Based Analysis for the Diagnosis of Alzheimer's Disease Using Structural Magnetic Resonance Image
- (2016) R. Sandanalakshmi et al. Journal of Medical Imaging and Health Informatics
- Optimizing Multiple Kernel Learning for the Classification of UAV Data
- (2016) Caroline Gevaert et al. Remote Sensing
- Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment
- (2015) Lele Xu et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Brain PET in the Diagnosis of Alzheimer’s Disease
- (2014) Charles Marcus et al. CLINICAL NUCLEAR MEDICINE
- Extracting Salient Brain Patterns for Imaging-Based Classification of Neurodegenerative Diseases
- (2014) Andrea Rueda et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis
- (2014) Xiaofeng Zhu et al. NEUROIMAGE
- Ensemble sparse classification of Alzheimer's disease
- (2012) Manhua Liu et al. NEUROIMAGE
- Hybrid dendritic computing with kernel-LICA applied to Alzheimer's disease detection in MRI
- (2011) Darya Chyzhyk et al. NEUROCOMPUTING
- The diagnosis of young-onset dementia
- (2010) Martin N Rossor et al. LANCET NEUROLOGY
- Cerebrospinal fluid and plasma biomarkers in Alzheimer disease
- (2010) Kaj Blennow et al. Nature Reviews Neurology
- Feature-based morphometry: Discovering group-related anatomical patterns
- (2009) Matthew Toews et al. NEUROIMAGE
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started