AIMC Journal:
BMC medical imaging

Showing 211 to 220 of 252 articles

A review on deep learning MRI reconstruction without fully sampled k-space.

BMC medical imaging Dec 24, 2021
BACKGROUND: Magnetic resonance imaging (MRI) is an effective auxiliary diagnostic method in clinical medicine, but it has always suffered from the problem of long acquisition time. Compressed sensing and parallel imaging are two common techniques to ...
Humans Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Pneumoconiosis computer aided diagnosis system based on X-rays and deep learning.

BMC medical imaging Dec 8, 2021
PURPOSE: The objective of this study is to construct a computer aided diagnosis system for normal people and pneumoconiosis using X-raysand deep learning algorithms.
Aged Aged, 80 and over Adult Humans Retrospective Studies Female Deep Learning Pneumoconiosis Male X-Rays Middle Aged Diagnosis, Computer-Assisted
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Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study.

BMC medical imaging Nov 25, 2021
BACKGROUND: Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among...
Thyroid Function Tests Retrospective Studies China Radiopharmaceuticals Sensitivity and Specificity Datasets as Topic Thyroid Diseases Female Predictive Value of Tests Sodium Pertechnetate Tc 99m Adult Male Humans Neural Networks, Computer
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A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets.

BMC medical imaging Nov 24, 2021
BACKGROUND: Most existing algorithms have been focused on the segmentation from several public Liver CT datasets scanned regularly (no pneumoperitoneum and horizontal supine position). This study primarily segmented datasets with unconventional liver...
Humans Liver Liver Neoplasms Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Pneumoperitoneum Imaging, Three-Dimensional Machine Learning Animals Datasets as Topic Contrast Media Swine
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UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BMC medical imaging Nov 22, 2021
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening mo...
Datasets as Topic Humans SARS-CoV-2 COVID-19 Deep Learning Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Development and validation of the 3D U-Net algorithm for segmentation of pelvic lymph nodes on diffusion-weighted images.

BMC medical imaging Nov 13, 2021
BACKGROUND: The 3D U-Net model has been proved to perform well in the automatic organ segmentation. The aim of this study is to evaluate the feasibility of the 3D U-Net algorithm for the automated detection and segmentation of lymph nodes (LNs) on pe...
Feasibility Studies Datasets as Topic Diffusion Magnetic Resonance Imaging Lymphatic Metastasis Prostatic Neoplasms Pelvis Humans Neural Networks, Computer Retrospective Studies Aged Male
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Accurate pancreas segmentation using multi-level pyramidal pooling residual U-Net with adversarial mechanism.

BMC medical imaging Nov 12, 2021
BACKGROUND: A novel multi-level pyramidal pooling residual U-Net with adversarial mechanism was proposed for organ segmentation from medical imaging, and was conducted on the challenging NIH Pancreas-CT dataset.
Contrast Media Datasets as Topic Pancreas Humans Neural Networks, Computer Tomography, X-Ray Computed
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Fully automated segmentation in temporal bone CT with neural network: a preliminary assessment study.

BMC medical imaging Nov 9, 2021
BACKGROUND: Segmentation of important structures in temporal bone CT is the basis of image-guided otologic surgery. Manual segmentation of temporal bone CT is time- consuming and laborious. We assessed the feasibility and generalization ability of a ...
Datasets as Topic Tomography, X-Ray Computed Humans Temporal Bone Image Processing, Computer-Assisted Neural Networks, Computer Surgery, Computer-Assisted
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GACDN: generative adversarial feature completion and diagnosis network for COVID-19.

BMC medical imaging Oct 21, 2021
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) causes tens of million infection world-wide. Many machine learning methods have been proposed for the computer-aided diagnosis between COVID-19 and community-acquired pneumonia (CAP) fro...
Diagnosis, Computer-Assisted COVID-19 Humans Deep Learning Tomography, X-Ray Computed SARS-CoV-2 Machine Learning
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Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors.

BMC medical imaging Oct 19, 2021
BACKGROUND: Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential fa...
Artifacts Neural Networks, Computer Phantoms, Imaging Coronary Artery Disease Tomography, X-Ray Computed Radiation Dosage Robotics Motion Plaque, Atherosclerotic Radiographic Image Interpretation, Computer-Assisted
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