Medical Annotation

There are several techniques of image annotation used to establish the AI model through machine learning. Some of them include cuboid annotation, polygon annotation and bounding box. However, semantic segmentation is the best demonstrative technique that provides the detailed findings with illnesses segmented and categorised in an individual class. Medical image segmentation aids to detect …

Semantic Segmentation for Medical Image – Single Class Read More »

Telemedicine is evolving rapidly and hence the need for quicker transmission of diagnostic clinical images and image processing arises. AI in healthcare has become highly significant with more accurate detection of illnesses using medical imaging datasets. As a result, it helps AI models to understand and track various types of illnesses using computer vision technology. …

Overview of Semantic Image Segmentation for Clinical Imaging Datasets Read More »

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 …

Role of Medical Image Annotation in AI Radiology Read More »

Image annotation in the medical sector is used for diagnosing the illnesses including blood clotting, brain tumours and other neurological disorders. With the help of the MRI or CT scan, ML models can detect illnesses especially if they are trained well with accurately annotated images. The brain injuries or other issues are well annotated and …

Medical Uses of Image Annotation Read More »