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Machine Learning for Medical Imaging

What's different between CT, MRI and PET?

Published 5 months agoΒ β€’Β 2 min read

Hi Reader,,

Welcome to the PYCAD newsletter, where every week you receive doses of machine learning and computer vision techniques and tools to help you learn how to build AI solutions to empower the most vulnerable members of our society, patients.

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What do you know about CT, MRI and PET scans?

In medical imaging, we work a lot on CT, MRI and PET modalities. Here’s a brief overview for you:

MRI (Magnetic Resonance Imaging), CT (Computed Tomography), and PET (Positron Emission Tomography) scans are all medical imaging techniques, but they differ significantly in their technology, usage, and what they show about the body.

  1. MRI (Magnetic Resonance Imaging):
  • Technology:

Uses strong magnetic fields and radio waves to create detailed images of the body.

  • Usage:

Especially useful for imaging soft tissues. Commonly used to diagnose brain tumors, spinal cord injuries, heart conditions, and joint problems.

  • Advantages:

Provides high-resolution images, particularly of soft tissue, and does not use ionizing radiation.

  • Limitations: More expensive and time-consuming than CT scans. It can be uncomfortable for claustrophobic patients due to the confined space and loud noise during the scan.
  1. CT (Computed Tomography) Scan:
  • Technology:

Utilizes X-rays to create detailed cross-sectional images (slices) of the body.

  • Usage:

Often used in emergencies due to its speed. It is useful for diagnosing fractures, tumors, internal injuries, and monitoring conditions like cancer.

  • Advantages:

Faster than MRI and provides excellent detail of bone structures as well as a good detail of soft tissues.

  • Limitations:

Involves exposure to ionizing radiation and may not be as effective as MRI in distinguishing between soft tissues.

  1. PET (Positron Emission Tomography) Scan:
  • Technology:

Involves injecting a small amount of radioactive material into the body. The scanner detects the energy emitted by the radioactive substance.

  • Usage:

Mainly used in cancer treatment, neurology, and cardiology. It helps to visualize metabolic processes in the body, such as cancer cell activity.

  • Advantages:

Provides functional information about how organs and tissues are working, which is not available through MRI or CT scans.

  • Limitations:

Lower spatial resolution compared to MRI and CT. The radioactive material may pose risks, though generally considered minimal.

In summary, MRI is excellent for soft tissue detail and doesn’t use radiation, CT is fast and good for imaging bone as well as soft tissue but involves radiation, and PET is unique in showing metabolic activity but has lower spatial resolution and involves radioactive tracers.

The choice among these depends on the specific medical situation and the information needed by the healthcare provider.

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We Can Help You with Your Next Medical Imaging Project

If your company or organization is looking to build a machine learning solution for a medical imaging problem, then feel free to reach out to us at:

​contact@pycad.co​

We can help you build a full ML solution from training to deployment with affordable rates!

You can check out some of the projects that we worked on here:

​https://pycad.co/portfolio and some of our clients case studies here.

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That's it for this week's edition, I hope you enjoyed it!

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Machine Learning for Medical Imaging

by Nour Islam Mokhtari from pycad.co

πŸ‘‰ Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | πŸ’‘ The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!

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