Graph of brain structures grading for early detection of Alzheimer's disease
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Abstract (arXiv)
Alzheimer's disease is the most common dementia leading to an irreversible neurodegenerative process. To date, subject revealed advanced brain structural alterations when the diagnosis is established. Therefore, an earlier diagnosis of this dementia is crucial although it is a challenging task. Recently, many studies have proposed biomarkers to perform early detection of Alzheimer's disease. Some of them have proposed methods based on inter-subject similarity while other approaches have investigated framework using intra-subject variability. In this work, we propose a novel framework combining both approaches within an efficient graph of brain structures grading. Subsequently, we demonstrate the competitive performance of the proposed method compared to state-of-the-art methods.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jul 2018.
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Citing papers per year: 2022: 3.
3 papers.
- 2022Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligencecited by 5
- 2022Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementiacited by 5
- 2022Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosiscited by 0
- 2022Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis28 Nov 2022
- 2022Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia25 Nov 2022
- 2022Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligence7 Jun 2022