AIMC Topic: Atlases as Topic

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Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

Nature reviews. Nephrology
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medic...

Deep learning vs. atlas-based models for fast auto-segmentation of the masticatory muscles on head and neck CT images.

Radiation oncology (London, England)
BACKGROUND: Impaired function of masticatory muscles will lead to trismus. Routine delineation of these muscles during planning may improve dose tracking and facilitate dose reduction resulting in decreased radiation-related trismus. This study aimed...

The NanoZoomer artificial intelligence connectomics pipeline for tracer injection studies of the marmoset brain.

Brain structure & function
We describe our connectomics pipeline for processing anterograde tracer injection data for the brain of the common marmoset (Callithrix jacchus). Brain sections were imaged using a batch slide scanner (NanoZoomer 2.0-HT) and we used artificial intell...

A Comprehensive Network Atlas Reveals That Turing Patterns Are Common but Not Robust.

Cell systems
Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to dis...

How many models/atlases are needed as priors for capturing anatomic population variations?

Medical image analysis
Many medical image processing and analysis operations can benefit a great deal from prior information encoded in the form of models/atlases to capture variations over a population in form, shape, anatomic layout, and image appearance of objects. Howe...

Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction.

NeuroImage
The specificity and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on preprocessing choices, such as the parcellation scheme used to define regions of interest (ROIs). In this study, we critically evaluate the effect of bra...

3D whole brain segmentation using spatially localized atlas network tiles.

NeuroImage
Detailed whole brain segmentation is an essential quantitative technique in medical image analysis, which provides a non-invasive way of measuring brain regions from a clinical acquired structural magnetic resonance imaging (MRI). Recently, deep conv...

A deep learning based method for large-scale classification, registration, and clustering of in-situ hybridization experiments in the mouse olfactory bulb.

Journal of neuroscience methods
BACKGROUND: The Allen Mouse Brain Atlas allows study of the brain's molecular anatomy at cellular scale, for thousands genes. To fully leverage this resource, one must register histological images of brain tissue - a task made challenging by the brai...

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

NeuroImage
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they ...