AIMC Topic: Tomography

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Research on missing value prediction of measured ERT data for coal mine based on a GRNN algorithm.

PloS one
In the process of long-term monitoring of the coal seam floor of a coal mining face using electrical resistivity tomography (ERT), the data loss caused by electrode disconnection adversely affects early warning of water inrush and prevents the identi...

Vulnerabilities of feature clustering in EIT radiomics.

Computers in biology and medicine
BACKGROUND: We aimed to determine whether unsupervised machine learning was able to discover latent and possibly clinically-relevant clusters, hidden in dynamic electrical impedance tomography (EIT) images within a population of mechanically ventilat...

A Comparative Evaluation of Microimpedance Tomography Reconstruction Algorithms for in Vitro Imaging.

ACS sensors
This paper presents the development of a novel miniature electrical impedance tomography (EIT) system made out of glass, along with the training, validation, and testing of an accompanying open-source machine learning image reconstruction model. Our ...

Adaptive k-sparse constrained dictionary learning strategy for bioluminescence tomography reconstruction.

Physics in medicine and biology
. Bioluminescence tomography (BLT) is a significant molecular imaging modality with promising potential in biomedical research. However, the reconstruction results of BLT are frequently sensitive and imprecise due to the light scattering effect and i...

3D electroacoustic tomography image enhancement using deep learning with the SAM-Med3D encoder.

Physics in medicine and biology
To overcome the limitations of electroacoustic tomography (EAT) in clinical settings-particularly the artifacts and distortions caused by limited-angle data acquisition-and enable accurate, efficient visualization of electric field distributions for ...

Review of GPU-based Monte Carlo simulation platforms for transmission and emission tomography in medicine.

Physics in medicine and biology
. Monte Carlo (MC) simulation remains the gold standard for modeling complex physical interactions in transmission and emission tomography, with graphic processing unit (GPU) parallel computing offering unmatched computational performance and enablin...

Multimodal information structuring with single-layer soft skins and high-density electrical impedance tomography.

Science robotics
The human skin can reliably capture a wide range of multimodal data over a large surface while providing a soft interface. Artificial technologies using microelectromechanical systems (MEMS) can emulate these biological functions but present numerous...

AI-assisted diffuse correlation tomography for identifying breast cancer.

Journal of biomedical optics
SIGNIFICANCE: Diffuse correlation tomography (DCT) is an emerging technique for the noninvasive measurement of breast microvascular blood flow, whereas its capability to categorize benign and malignant breast lesions has not been extensively validate...

An explainable artificial intelligence framework for weaning outcomes prediction using features from electrical impedance tomography.

Computer methods and programs in biomedicine
BACKGROUND: Prolonged mechanical ventilation (PMV) might cause ventilator-associated pneumonia and diaphragmatic injury, and may lead to worsening clinical weaning outcomes. The present study proposes a comprehensive machine learning (ML) framework f...

Deep prior embedding method for Electrical Impedance Tomography.

Neural networks : the official journal of the International Neural Network Society
This paper presents a novel deep learning-based approach for Electrical Impedance Tomography (EIT) reconstruction that effectively integrates image priors to enhance reconstruction quality. Traditional neural network methods often rely on random init...