Role of Medical Image Annotation in AI Radiology

Most clinicians and patients today rely on telemedicine to overcome communication barriers. Therefore, it is important to hire medical content translators as they can deal with multilingual communication with the help of telemedicine.

As far as medical image annotation in telemedicine is concerned, it has provided a new dimension to AI in radiology with a massive amount of label data to the appropriate development of machine learning.

Record Documentation

Medical image annotation aids in covering distinct documents such as files and texts to ensure that the data is recognisable and logical to the machine. As the medical records comprise patient’s data and details on their health conditions, it can be utilised for training the ML models. When you annotate the clinical records using the text annotation and accurate metadata or extra notes, it utilises such data for the development of machine learning.

Types of Documents for Annotation

The annotators with years of experience can label those documents accurately and at the same time maintain the confidentiality and privacy of data. Some of the main types of data used for image annotation includes CT scan, X-Ray, MRI, DICOM, ultrasound, videos and many other images.

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