AIMC Topic: Imaging, Three-Dimensional

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Deep-Learning-Based Automated Neuron Reconstruction From 3D Microscopy Images Using Synthetic Training Images.

IEEE transactions on medical imaging
Digital reconstruction of neuronal structures from 3D microscopy images is critical for the quantitative investigation of brain circuits and functions. It is a challenging task that would greatly benefit from automatic neuron reconstruction methods. ...

Deep learning-based plane pose regression in obstetric ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a major challenge in skill acquisition. We aim to build a US plane local...

Machine learning and geometric morphometrics to predict obstructive sleep apnea from 3D craniofacial scans.

Sleep medicine
BACKGROUND: Obstructive sleep apnea (OSA) remains massively underdiagnosed, due to limited access to polysomnography (PSG), the highly complex gold standard for diagnosis. Performance scores in predicting OSA are evaluated for machine learning (ML) a...

Deep-learning-based 3D cellular force reconstruction directly from volumetric images.

Biophysical journal
The forces exerted by single cells in the three-dimensional (3D) environments play a crucial role in modulating cellular functions and behaviors closely related to physiological and pathological processes. Cellular force microscopy (CFM) provides a f...

Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures.

Contrast media & molecular imaging
In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning...

Artificial intelligence deep learning for 3D IC reliability prediction.

Scientific reports
Three-dimensional integrated circuit (3D IC) technologies have been receiving much attention recently due to the near-ending of Moore's law of minimization in 2D IC. However, the reliability of 3D IC, which is greatly influenced by voids and failure ...

Tri-view two-photon microscopic image registration and deblurring with convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Two-photon fluorescence microscopy has enabled the three-dimensional (3D) neural imaging of deep cortical regions. While it can capture the detailed neural structures in the x-y image space, the image quality along the depth direction is lower becaus...

Deep learning-based automatic segmentation of images in cardiac radiography: A promising challenge.

Computer methods and programs in biomedicine
BACKGROUND: Due to the advancement of medical imaging and computer technology, machine intelligence to analyze clinical image data increases the probability of disease prevention and successful treatment. When diagnosing and detecting heart disease, ...

Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets.

PLoS computational biology
Segmenting three-dimensional (3D) microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth, and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed, which claim ...

Deep learning -- promises for 3D nuclear imaging: a guide for biologists.

Journal of cell science
For the past century, the nucleus has been the focus of extensive investigations in cell biology. However, many questions remain about how its shape and size are regulated during development, in different tissues, or during disease and aging. To trac...