Computed tomography and deep learning

Can AI read a CT scan?
In a previous study, the team had developed an AI algorithm to take chest CT images and convert that data into information about body composition: skeletal muscle mass, fat mass, muscle lipid content — that sort of thing..
How is deep learning used in medical imaging?
Accordingly, the deep learning algorithm gets a lot of attention these days to solve various problems in medical imaging fields.
One example is to detect disease or abnormalities from X-ray images and classify them into several disease types or severities in radiology [4,5]..
Why deep learning in medical imaging?
Accordingly, the deep learning algorithm gets a lot of attention these days to solve various problems in medical imaging fields.
One example is to detect disease or abnormalities from X-ray images and classify them into several disease types or severities in radiology [4,5]..
Why do we use deep learning?
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example.
Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost..
Accordingly, the deep learning algorithm gets a lot of attention these days to solve various problems in medical imaging fields.
One example is to detect disease or abnormalities from X-ray images and classify them into several disease types or severities in radiology [4,5].
Deep learning can accommodate massive medical imaging databases, perform data analysis across multiple modes, transmit neural network learning across different data sets, and usually include partially labeled data, corrected linear units [19], convolutional neural networks.
Healthcare: Deep learning is used to analyze medical images and patient data, to improve diagnosis and treatment, and to identify potential health risks.
Applications include cancer diagnosis, drug discovery, and personalized medicine.

Deep learning enables image classification and segmentation in imaging [11]. Among non-invasive modalities, computed tomography angiography (CTA) is an emerging modality with efficacy and accuracy paralleling other contemporary modalities.

May 17, 2023Deep learning enables image classification and segmentation in imaging [11]. Among non-invasive modalities, computed tomography angiography (CTA) AbstractIntroduction and backgroundReviewConclusions

In this paper, we present a new deep learning framework for 3-D tomographic reconstruction. To this end, we map filtered back-projection-type algorithms to

Categories

Computed tomography and deep learning

Can AI read a CT scan?

How is deep learning used in medical imaging?

Why deep learning in medical imaging?

Why do we use deep learning?