AIMC Journal:
BMC medical imaging

Showing 181 to 190 of 252 articles

Motion artefact reduction in coronary CT angiography images with a deep learning method.

BMC medical imaging Oct 28, 2022
BACKGROUND: The aim of this study was to investigate the ability of a pixel-to-pixel generative adversarial network (GAN) to remove motion artefacts in coronary CT angiography (CCTA) images.
Computed Tomography Angiography Retrospective Studies Deep Learning Coronary Angiography Artifacts Humans Algorithms
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Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning.

BMC medical imaging Oct 15, 2022
BACKGROUND: Nowadays doctors and radiologists are overwhelmed with a huge amount of work. This led to the effort to design different Computer-Aided Diagnosis systems (CAD system), with the aim of accomplishing a faster and more accurate diagnosis. Th...
Neural Networks, Computer COVID-19 Humans COVID-19 Testing Computers X-Rays Deep Learning
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AbdomenNet: deep neural network for abdominal organ segmentation in epidemiologic imaging studies.

BMC medical imaging Sep 17, 2022
BACKGROUND: Whole-body imaging has recently been added to large-scale epidemiological studies providing novel opportunities for investigating abdominal organs. However, the segmentation of these organs is required beforehand, which is time consuming,...
Water Cohort Studies Humans Neural Networks, Computer Abdomen Magnetic Resonance Imaging
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Research on imbalance machine learning methods for MRWI soft tissue sarcoma data.

BMC medical imaging Aug 26, 2022
BACKGROUND: Soft tissue sarcoma is a rare and highly heterogeneous tumor in clinical practice. Pathological grading of the soft tissue sarcoma is a key factor in patient prognosis and treatment planning while the clinical data of soft tissue sarcoma ...
Sarcoma Soft Tissue Neoplasms Machine Learning Algorithms Humans
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Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images.

BMC medical imaging Jul 30, 2022
BACKGROUND: Corona Virus Disease 2019 (COVID-19) first appeared in December 2019, and spread rapidly around the world. COVID-19 is a pneumonia caused by novel coronavirus infection in 2019. COVID-19 is highly infectious and transmissible. By 7 May 20...
Deep Learning X-Rays Humans COVID-19 Neural Networks, Computer SARS-CoV-2
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SAFARI: shape analysis for AI-segmented images.

BMC medical imaging Jul 22, 2022
BACKGROUND: Recent developments to segment and characterize the regions of interest (ROI) within medical images have led to promising shape analysis studies. However, the procedures to analyze the ROI are arbitrary and vary by study. A tool to transl...
Humans Artificial Intelligence Algorithms Image Processing, Computer-Assisted Glioblastoma
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Multimodal image translation via deep learning inference model trained in video domain.

BMC medical imaging Jul 14, 2022
BACKGROUND: Current medical image translation is implemented in the image domain. Considering the medical image acquisition is essentially a temporally continuous process, we attempt to develop a novel image translation framework via deep learning tr...
Cone-Beam Computed Tomography Image Processing, Computer-Assisted Signal-To-Noise Ratio Reproducibility of Results Humans Deep Learning
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Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.

BMC medical imaging Jul 9, 2022
OBJECTIVES: Accurate contouring of the clinical target volume (CTV) is a key element of radiotherapy in cervical cancer. We validated a novel deep learning (DL)-based auto-segmentation algorithm for CTVs in cervical cancer called the three-channel ad...
Image Processing, Computer-Assisted Reactive Oxygen Species Radiotherapy Planning, Computer-Assisted Uterine Cervical Neoplasms Deep Learning Algorithms Female Humans
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Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?

BMC medical imaging Jun 7, 2022
BACKGROUND: The aim of the study was to predict the probability of intensive care unit (ICU) care for inpatient COVID-19 cases using clinical and artificial intelligence segmentation-based volumetric and CT-radiomics parameters on admission.
Critical Care Tomography, X-Ray Computed COVID-19 SARS-CoV-2 Humans Deep Learning Retrospective Studies Artificial Intelligence Bayes Theorem
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DNL-Net: deformed non-local neural network for blood vessel segmentation.

BMC medical imaging Jun 6, 2022
BACKGROUND: The non-local module has been primarily used in literature to capturing long-range dependencies. However, it suffers from prohibitive computational complexity and lacks the interactions among positions across the channels.
Neural Networks, Computer Disease Progression Humans Image Processing, Computer-Assisted Pyramidal Tracts
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