Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease

Wang, Min; Cui, Bixiao; Shan, Yi; Yang, Hongwei; Yan, Zhuangzhi; Sundar, Lalith Kumar Shiyam; Alberts, Ian; Rominger, Axel; Wendler, Thomas; Shi, Kuangyu; Ma, Yan; Jiang, Jiehui; Lu, Jie

doi:10.1109/jbhi.2022.3193190

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…After ROI extraction, the reviewed studies commonly use GM tissue mean intensities, or volumes, of brain ROIs as features from PET, MRI, fMRI or other modalities [198]. Other measures include subcortical volumes [199,200], grey matter densities [201,202], cortical thickness [203,204], brain glucose metabolism [205,206], cerebral amyloid-β accumulation [207,208], and the average regional CMRGlc [209] for PET. The hippocampus is of particular interest in the reviewed papers; ROI-based methods have used 3D data and morphological measurements of its cortical thickness, curvature, surface area, and volume.…”

Section: Roi-basedmentioning

confidence: 99%

A Survey of Deep Learning for Alzheimer’s Disease

Zhou

Wang

et al. 2023

MAKE

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Alzheimer’s and related diseases are significant health issues of this era. The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. This paper surveys deep learning literature related to Alzheimer’s disease, mild cognitive impairment, and related diseases from 2010 to early 2023. We identify the major types of unsupervised, supervised, and semi-supervised methods developed for various tasks in this field, including the most recent developments, such as the application of recurrent neural networks, graph-neural networks, and generative models. We also provide a summary of data sources, data processing, training protocols, and evaluation methods as a guide for future deep learning research into Alzheimer’s disease. Although deep learning has shown promising performance across various studies and tasks, it is limited by interpretation and generalization challenges. The survey also provides a brief insight into these challenges and the possible pathways for future studies.

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