AIMC Topic: Tomography, X-Ray Computed

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One deep learning local-global model based on CT imaging to differentiate between nodular cryptococcosis and lung cancer which are hard to be diagnosed.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVES: We aim to evaluate a deep learning (DL) model and radiomic model for preoperative differentiation of nodular cryptococcosis from solitary lung cancer in patients with malignant features on CT images.

Deep learning network for medical volume data segmentation based on multi axial plane fusion.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: High-dimensional data generally contains more accurate information for medical image, e.g., computerized tomography (CT) data can depict the three dimensional structure of organs more precisely. However, the data in high-dim...

Computed Tomography Image under Convolutional Neural Network Deep Learning Algorithm in Pulmonary Nodule Detection and Lung Function Examination.

Journal of healthcare engineering
The objective of this study was to perform segmentation and extraction of CT images of pulmonary nodules based on convolutional neural networks (CNNs). The Mask-RCNN algorithm model is a typical end-to-end image segmentation model, which uses the R-F...

Deep learning model for automatic contouring of cardiovascular substructures on radiotherapy planning CT images: Dosimetric validation and reader study based clinical acceptability testing.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Large radiotherapy (RT) planning imaging datasets with consistently contoured cardiovascular structures are essential for robust cardiac radiotoxicity research in thoracic cancers. This study aims to develop and validate a hig...

Computed Tomography Perfusion-Based Prediction of Core Infarct and Tissue at Risk: Can Artificial Intelligence Help Reduce Radiation Exposure?

Stroke
BACKGROUND AND PURPOSE: We explored the feasibility of automated, arterial input function independent, vendor neutral prediction of core infarct, and penumbral tissue using complete and partial computed tomographic perfusion data sets through neural ...

GACDN: generative adversarial feature completion and diagnosis network for COVID-19.

BMC medical imaging
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...

Deep Learning Algorithms-Based CT Images in Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction.

Journal of healthcare engineering
CT image information data under deep learning algorithms was adopted to evaluate small airway function and analyze the clinical efficacy of different glucocorticoid administration ways in asthmatic children with small airway obstruction. The Res-NET ...

Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease.

Computational and mathematical methods in medicine
In March 2020, the World Health Organization announced the COVID-19 pandemic, its dangers, and its rapid spread throughout the world. In March 2021, the second wave of the pandemic began with a new strain of COVID-19, which was more dangerous for som...

Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Attenuation correction can improve the quantitative accuracy of single-photon emission computed tomography (SPECT) images. Existing SPECT-only systems normally can only provide non-attenuation corrected (NC) images which are susceptible t...

Deep Learning-Based Computed Tomography Imaging to Diagnose the Lung Nodule and Treatment Effect of Radiofrequency Ablation.

Journal of healthcare engineering
This study aimed to detect and diagnose the lung nodules as early as possible to effectively treat them, thereby reducing the burden on the medical system and patients. A lung computed tomography (CT) image segmentation algorithm was constructed base...