AIMC Topic: Tomography, X-Ray Computed

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A stacked ensemble for the detection of COVID-19 with high recall and accuracy.

Computers in biology and medicine
The main challenges for the automatic detection of the coronavirus disease (COVID-19) from computed tomography (CT) scans of an individual are: a lack of large datasets, ambiguity in the characteristics of COVID-19 and the detection techniques having...

Harnessing clinical annotations to improve deep learning performance in prostate segmentation.

PloS one
PURPOSE: Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinicall...

Artificial intelligence in medical imaging: implications for patient radiation safety.

The British journal of radiology
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic ...

Medical imaging and computational image analysis in COVID-19 diagnosis: A review.

Computers in biology and medicine
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough, and chronic fatigue, amongst others. The disease may be asymptomatic i...

Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.

Journal of applied clinical medical physics
PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation...

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement...