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Healthcare – MRI Machine Issues

Reasons for malfunctioning or underperforming MRI machine.

This fishbone describes the different problems of an MRI machine and its causes

Magnetic resonance imaging (MRI) with the help of a large magnet and radio waves, takes images of the internal organs of our body. It enables the health care professionals or medical practitioners to diagnose several medical conditions. MRIs are very useful for examining the brain and spinal cord.

A faulty MRI machine generates a huge amount of heat and intense noise. This machine has several cooing heads which lower its temperature. Abnormal shutdown of the machine, loud noise, poor quality images, locked up machine leave the technician in a perplexed state of mind. Several potential factors like poor maintenance of cooling head and coil, power outage, poor performance of cooling head, and out of date software may affect its performance.

MRI Machine Issues
Machine Locked up

  •    Under performing cooling components

Intense vibrations/ noise

  •    Poor monitoring of cold head
  •    Cold head not working properly

System shut down and restart

  •    Power issues
    • Internal computer malfunctions
    • Out of date software
    • Power surge due to storm
    • Power outage

  Image artifacts/ quality

  •    Wear and tear of the coil
  •    Poor maintenance of the coil
  •    Damaged coil

This Ishikawa diagram on MRI Machine Issues contains many  parent causes with child causes underneath. It’s well organized, simple and easy to understand. The underlying fishbone template is customizable and user friendly.

Who should use the MRI Machine Issues template?

  • This fishbone template provides helpful guidance to one who wants to know the causes of a malfunctioning MRI Machine.

Why use this template?

  • The MRI Machine fishbone  template describes the causes why MRI Machine gets shut down, produces image artifacts, large noise etc.
  • Customize, extend and reuse this template using smartQED.
  • Design and create your own templates for in-depth visual problem analysis in smartQED.

Curated from community experience and public sources:

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