AIMC Topic: Phantoms, Imaging

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Deep Learning-Based Image Conversion Improves the Reproducibility of Computed Tomography Radiomics Features: A Phantom Study.

Investigative radiology May 1, 2022
OBJECTIVES: This study aimed to evaluate the usefulness of deep learning-based image conversion to improve the reproducibility of computed tomography (CT) radiomics features.
Tomography, X-Ray Computed Reproducibility of Results Phantoms, Imaging Deep Learning Tomography Scanners, X-Ray Computed Image Processing, Computer-Assisted
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Quantitative endoscopic photoacoustic tomography using a convolutional neural network.

Applied optics Apr 1, 2022
Endoscopic photoacoustic tomography (EPAT) is a catheter-based hybrid imaging modality capable of providing structural and functional information of biological luminal structures, such as coronary arterial vessels and the digestive tract. The recover...
Image Processing, Computer-Assisted Phantoms, Imaging Neural Networks, Computer Tomography, X-Ray Computed Endoscopy
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3D k-space reflectance fluorescence tomography via deep learning.

Optics letters Mar 15, 2022
We report on the potential to perform image reconstruction in 3D k-space reflectance fluorescence tomography (FT) using deep learning (DL). Herein, we adopt a modified AUTOMAP architecture and develop a training methodology that leverages an open-sou...
Deep Learning Tomography Monte Carlo Method Phantoms, Imaging Image Processing, Computer-Assisted
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First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels.

Investigative radiology Feb 1, 2022
OBJECTIVE: The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evalu...
Artificial Intelligence Computers Photons Tomography, X-Ray Computed Phantoms, Imaging
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Towards Fast Region Adaptive Ultrasound Beamformer for Plane Wave Imaging Using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Automatic learning algorithms for improving the image quality of diagnostic B-mode ultrasound (US) images have been gaining popularity in the recent past. In this work, a novel convolutional neural network (CNN) is trained using time of flight correc...
Phantoms, Imaging Ultrasonography Neural Networks, Computer Algorithms Diagnostic Tests, Routine
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Robotic Cytology using Extra-Fine Needles : -Proposal of Puncture Control Strategy for Increasing Collection Amount.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Fine needle aspiration cytology requires accurate needle insertion into a tumor and sufficient amount collection of samples, which highly depends on the skill of the physician. The advantage of the diagnosis is to minimize the tissue damage with the ...
Phantoms, Imaging Needles Robotics Robotic Surgical Procedures Punctures
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Model reduction in acoustic inversion by artificial neural network.

The Journal of the Acoustical Society of America Nov 1, 2021
In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model is a prominent factor for high-quality image reconstruction, but it can...
Phantoms, Imaging Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Acoustics Neural Networks, Computer
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IMPROVEMENTS OF 111IN SPECT IMAGES RECONSTRUCTED WITH SPARSELY ACQUIRED PROJECTIONS BY DEEP LEARNING GENERATED SYNTHETIC PROJECTIONS.

Radiation protection dosimetry Oct 12, 2021
The aim was to improve single-photon emission computed tomography (SPECT) quality for sparsely acquired 111In projections by adding deep learning generated synthetic intermediate projections (SIPs). Method: The recently constructed deep convolutional...
Deep Learning Tomography, Emission-Computed, Single-Photon Indium Radioisotopes Image Processing, Computer-Assisted Phantoms, Imaging
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PULMONARY NODULE DETECTION IN CHEST CT USING A DEEP LEARNING-BASED RECONSTRUCTION ALGORITHM.

Radiation protection dosimetry Oct 12, 2021
This study's aim was to assess whether deep learning image reconstruction (DLIR) techniques are non-inferior to ASIR-V for the clinical task of pulmonary nodule detection in chest computed tomography. Up to 6 (range 3-6, mean 4.2) artificial lung nod...
Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Phantoms, Imaging Tomography, X-Ray Computed Algorithms Deep Learning
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A convolutional neural network algorithm for breast tumor detection with magnetic detection electrical impedance tomography.

The Review of scientific instruments Jun 1, 2021
Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of patients. Magnetic Detection Electrical Impedance Tomography (MDEIT) based on the Convolutional Neu...
Tomography Female Breast Neoplasms Image Processing, Computer-Assisted Neural Networks, Computer Humans Phantoms, Imaging Electric Impedance Algorithms
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