Chief.AI Blog

This is a step by step guide for radiologists (veteran and aspiring) to help build a plan for utilizing AI to improve efficiency in radiology operations.

1. If you are a radiologist or diagnostic physician, you can start by selecting an AI diagnostic service that is suitable for your needs, such as Chief.AI, which provides specialised services for tumour segmentation in diagnostic images.
2. Set up the AI diagnostic service by integrating it with your existing medical diagnostic machines using a RESTFUL API. This will allow the AI service to access and analyse the diagnostic images.
3. Prepare the diagnostic images for analysis by ensuring they are of high quality and properly formatted. This may include adjusting the contrast, brightness, and resolution of the images.
4. Once the images are ready, use the AI diagnostic service to analyse them. The AI algorithms will quickly identify potential tumours and other abnormalities in the images, providing a list of potential diagnoses.
5. Review the results provided by the AI service, and use your expertise as a radiologist to make a final diagnosis. The AI service can assist in the interpretation of diagnostic images, which can improve the accuracy of the diagnosis.
6. After the diagnosis, you can use the results provided by the AI service to create a treatment plan for the patient.
7. Finally, monitor the patient’s progress and adjust the treatment plan as needed based on the patient’s response to treatment.
8. Continuously monitor the performance of the AI service and adjust the parameters accordingly and keep the service updated with the latest advancements in AI technology, to ensure the most accurate and efficient diagnoses.

There are several key areas in which radiology workload on CT scan images versus MRI images differs:

1. Image quality: CT scans produce images that are highly detailed and precise, with a high level of contrast between different types of tissue. MRI images, on the other hand, are typically less detailed and less precise, but they provide better visualization of soft tissue structures.
2. Imaging modality: CT scans use X-rays to produce images, while MRI uses a combination of a magnetic field and radio waves. The two imaging modalities have different strengths and weaknesses, and they are used for different types of diagnoses.
3. Scanning time: CT scans are typically faster to complete than MRI scans, which can take up to an hour. This can affect the workload for radiologists, as they may need to review a larger number of CT images in a shorter period of time.
4. Contrast agents: CT scans typically require the use of contrast agents to enhance the visibility of certain structures in the images. MRI does not require the use of contrast agents, but sometimes it may use them to help with specific diagnoses.
5. Patient comfort: CT scans require the patient to lie still during the scan, while MRI allows the patient to move around. This can affect the patient’s comfort level and the radiologist’s ability to obtain clear images.

In summary, CT scans are used for detailed, high-contrast images of bones and other hard tissues, while MRI is used for better visualization of soft tissue structures. CT scans are faster to complete and require the use of contrast agents, while MRI is a longer process and doesn’t require them. Radiologists need to adapt their workflow to the different peculiarities of each modality, and also need to be familiar with the indications of use, and the strengths and limitations of each modality. AI can be adapted to accelerate diagnoses on both imaging modalities.

By following these steps, radiologists can use AI to diagnose patients more efficiently, reducing the time it takes to make a diagnosis and potentially leading to faster treatment and better outcomes for patients.