. Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-prin...
Diagnostic and interventional imaging
May 13, 2024
PURPOSE: The purpose of this study was to evaluate the achievable radiation dose reduction of an ultra-high resolution computed tomography (UHR-CT) scanner using deep learning reconstruction (DLR) while maintaining temporal bone image quality equal t...
The success of deep learning methodologies hinges upon the availability of meticulously labeled extensive datasets. However, when dealing with medical images, the annotation process for such abundant training data often necessitates the involvement o...
To mitigate systematic errors in magnetic resonance fingerprinting (MRF), the precomputed dictionary is usually computed with minimal granularity across the entire range of tissue parameters. However, the dictionary grows exponentially with the numbe...
Deep learning can be used effectively to predict participants' age from brain magnetic resonance imaging (MRI) data, and a growing body of evidence suggests that the difference between predicted and chronological age-referred to as brain-predicted ag...
To improve the recognition effect of the folk dance image recognition model and put forward new suggestions for teachers' teaching strategies, this study introduces a Deep Neural Network (DNN) to optimize the folk dance training image recognition mod...
The process of image fusion is the process of enriching an image and improving the image's quality, so as to facilitate the subsequent image processing and analysis. With the increasing importance of image fusion technology, the fusion of infrared an...
BACKGROUND: Currently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We aimed to improve the performance of esophagus segmentation in deep learning by applying a strategy t...
Computer methods and programs in biomedicine
May 11, 2024
BACKGROUND AND OBJECTIVE: Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinic...
Over the past two decades, machine analysis of medical imaging has advanced rapidly, opening up significant potential for several important medical applications. As complicated diseases increase and the number of cases rises, the role of machine-base...
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