AI and Machine Learning in medical imaging is becoming more imperative with precise diagnosis of various diseases making the treatment and care process at hospitals more effective. And to train the AI model for medical imaging data analysis, high-quality training data sets is required to train the machine learning model and get the accurate results when used in real-life diagnosis. Cogito explained here how these medical images are annotated with different types of image annotation techniques.
Bounding Box for X-rays Image Analysis
Bounding box annotation is the process of annotating the area of interest in the x-rays images like fractured bones. This image annotation technique helps radiologist or doctors easily detect such ailment and make the right decision to provide the timely and right treatment.
Semantic Segmentation for Medical Images
Semantic segmentation is another image annotation technique used to annotate the medical images like X-rays, MRI or CT Scans. This image annotation technique can detect the malady with in-depth analysis of the various types of diseases. Cogito provides the semantic image annotation to precisely annotate the x-rays and other medical images as per the machine learning model needs.
Polygon Annotation for Dental Medical Imaging
Polygon image annotation in dentistry for medical imagining analysis is used to diagnosis the diseases in teeth. Actually, teeth are in irregular shapes, and polygon annotation can annotate such coarse shaped objects to make them recognizable to machines. Cogito works with highly experienced dentist to annotate the various types of teeth with precise diagnosis of the diseases.
Image Annotation for Kidney Disease Diagnosis
The semantic segmentation image annotation technique is also used to annotate the affected areas in the kidney to diagnosis the diseases. Medical imaging AI companies use such data to train the machine learning model learn how to detect the different maladies in the kidney and forecast the possible diseases helping doctors to take quick remedial actions to cure such deadly diseases.
Image Annotation for Cancer Cells Detection
Similarly, in cancel cell detection image annotation technique is used annotate the cells infected with cancer in the blood. The process is done precisely, and Cogito works with well-trained and experienced doctors or radiologist to annotate such blood cells to precisely spot the cancers symptoms in the patients. And after annotating such medical cancer cells images, it becomes for the machines to detect and recognize such maladies at faster speed and better accuracy.
Cogito provides the high-quality training datasets for deep learning for medical image analysis by AI models. It can annotate all types of medical images, for machine learning in healthcare. Cogito can provide the best quality annotated data sets processed in a highly secured environment. It is expert in image annotation and can use the different types and techniques of data annotation to make the different types of objects or things of interest recognizable to machine through computer vision.
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