Brain atlas

Brain atlas

A brain atlas is a comprehensive model of the brain that includes labeled structures, allowing for accurate identification and analysis of specific regions. It is often used in research and medical settings to aid in the understanding and diagnosis of neurological conditions. The atlas may be created through various methods, such as automated anatomical labeling, and can serve as a template for brain imaging and analysis. A brain atlas-based method refers to a technique or approach that utilizes a brain atlas in its methodology.From: Imaging of the Pelvis, Musculoskeletal System, and Special Applications to CAD [2019], Hybrid rendering of exploded views for medical image atlas visualization [2018], Multivariate Analysis of Ischaemic Lesions Using Computed Tomography and CT Perfusion Imaging: Critical Review [2023]

Deep Learning Algorithms for Brain Image Analysis

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Published in Mridu Sahu, G. R. Sinha, Brain and Behavior Computing, 2021

Sai Darahas Akkineni, S. P. K. Karri

One of the key goals in neuroimaging research is to understand the relationships between brain structures and corresponding functions [21]. The brain atlas acts as a 3D coordinate reference system having canonical representations of the brain anatomy. Various factors including genetics, age, and gender contribute to the construction of large population-based atlases. These atlases are intended to provide an accurate comprehensive description of the brain by incorporating multi-modal data from PET, functional MRI, etc. Reference [22] designed a probabilistic model framework to construct deformable templates. The neural network trained provides an efficient alignment of images to these templates. A deep residual regression network was proposed in [23] using a bi-variant geodesic distance-based loss function that learns to register the input volumes and then a correction network facilitates a forward propagation through the network.

Hybrid rendering of exploded views for medical image atlas visualization

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Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2018

Tim McGraw, Alejandro Guayaquil-Sosa

Surfaces were extracted from the automated anatomical labelling (AAL) brain atlas which has labels for 116 grey matter structures and a template image registered into the same coordinate system (Tzourio-Mazoyer et al. 2002). A slice of the atlas is shown in Figure 1. We further group the 116 labels into brain hemispheres (left, bilateral, right) and brain lobes (listed in Table 1).

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Deep Learning Algorithms for Brain Image Analysis

Hybrid rendering of exploded views for medical image atlas visualization