AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Virtual Transcriptomics: Noninvasive Phenotyping of Atherosclerosis by Decoding Plaque Biology From Computed Tomography Angiography Imaging.
Arteriosclerosis, thrombosis, and vascular biology
Mar 11, 2021
[Figure: see text].
Feasibility Studies
Coronary Vessels
Plaque, Atherosclerotic
Oligonucleotide Array Sequence Analysis
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Computed Tomography Angiography
Phenotype
Humans
Female
Artificial Intelligence
Aged
Male
Gene Expression Profiling
Transcriptome
Pilot Projects
Models, Genetic
Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms.
European radiology
Mar 10, 2021
OBJECTIVES: To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebra...
Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection.
IEEE transactions on medical imaging
Mar 2, 2021
Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneumonia using chest X-rays can be of significant value for large-scale screening and epidemic preventio...
Accurately Discriminating COVID-19 from Viral and Bacterial Pneumonia According to CT Images Via Deep Learning.
Interdisciplinary sciences, computational life sciences
Feb 27, 2021
Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films brings a lot of concentration and time for doctors. Therefore, it is necessary to develop an automatic ...
Intraoral radiograph anatomical region classification using neural networks.
International journal of computer assisted radiology and surgery
Feb 24, 2021
PURPOSE: Dental radiography represents 13% of all radiological diagnostic imaging. Eliminating the need for manual classification of digital intraoral radiographs could be especially impactful in terms of time savings and metadata quality. However, a...
JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 24, 2021
Recently, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in over 200 countries, influencing billions of humans. To control the infection, identifying and separating the infected people is the most crucial step. The main diagnos...
The future of CT: deep learning reconstruction.
Clinical radiology
Feb 23, 2021
There have been substantial advances in computed tomography (CT) technology since its introduction in the 1970s. More recently, these advances have focused on image reconstruction. Deep learning reconstruction (DLR) is the latest complex reconstructi...
Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.
The British journal of radiology
Feb 22, 2021
OBJECTIVES: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR).
Male
Middle Aged
Neoplasms
Deep Learning
Female
Aged
Aged, 80 and over
Adult
Signal-To-Noise Ratio
Postoperative Period
Whole Body Imaging
Contrast Media
Radiographic Image Interpretation, Computer-Assisted
Quality Control
Radiation Dosage
Humans
Algorithms
Prospective Studies
Tomography, X-Ray Computed
Evaluating treatment response to neoadjuvant chemoradiotherapy in rectal cancer using various MRI-based radiomics models.
BMC medical imaging
Feb 16, 2021
BACKGROUND: To validate and compare various MRI-based radiomics models to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) of rectal cancer.
DON: Deep Learning and Optimization-Based Framework for Detection of Novel Coronavirus Disease Using X-ray Images.
Interdisciplinary sciences, computational life sciences
Feb 15, 2021
In the hospital, a limited number of COVID-19 test kits are available due to the spike in cases every day. For this reason, a rapid alternative diagnostic option should be introduced as an automated detection method to prevent COVID-19 spreading amon...
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