BACKGROUND: Two deep learning image reconstruction (DLIR) techniques from two different computed tomography (CT) vendors have recently been introduced into clinical practice.
This paper introduces a deep learning based methodology for analyzing the self-assembled, fractal-like structures formed in evaporated droplets. To this end, an extensive image database of such structures of the plant extract Viscum album Quercus [Fo...
X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the ex...
BACKGROUND AND OBJECTIVE: Automatic segmentation and annotation of medical image plays a critical role in scientific research and the medical care community. Automatic segmentation and annotation not only increase the efficiency of clinical workflow,...
We aim to synthesize brain time-of-flight (TOF) PET images/sinograms from their corresponding non-TOF information in the image space (IS) and sinogram space (SS) to increase the signal-to-noise ratio (SNR) and contrast of abnormalities, and decrease ...
Computer methods and programs in biomedicine
Sep 9, 2022
BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis and treatment planning of orthodontic patients. Artificial intelligence, especially deep-learning t...
Segmentation of the liver and tumours from computed tomography (CT) scans is an important task in hepatic surgical planning. Manual segmentation of the liver and tumours is a time-consuming and labour-intensive task; therefore, a fully automated meth...
Deep neural networks have shown great improvements in low-dose computed tomography (CT) denoising. Early algorithms were primarily optimized to obtain an accurate image with low distortion between the denoised image and reference full-dose image at t...
To propose a novel deep learning-based method called RG-Net (reconstruction and generation network) for highly accelerated MR parametric mapping by undersampling k-space and reducing the acquired contrast number simultaneously.The proposed framework ...
Artificial intelligence is rapidly expanding in all technological fields. The medical field, and especially diagnostic imaging, has been showing the highest developmental potential. Artificial intelligence aims at human intelligence simulation throug...
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