Applications of Artificial Intelligence in Medical Images Analysis

There are several imaging modalities used for obtaining the images of the internal parts of the human body. Some modalities such as angiography require invasive procedure to obtain images using contrast agent for clear visualization of the tissue of interest. The images obtained using different modalities are highly unstructured, which makes it difficult for inexperienced medical practitioner to derive the value of the unstructured data. Consequently, the use of artificial intelligence (AI) in medical imaging research has tremendously increased over the past few years for deriving the value out of data of interest. However, the obtained images must be processed before performing deep learning based analysis, since the images may contain noise or may be of poor quality due to capturing devices or technicians. In addition, several image augmentation methods can also be applied to prepare the augmented data. The AI serves for several purposes such as classification of patients into normal and abnormal categories, detection of lesions in the image or segmentation of detected lesion. The use of AI has shown promising results in the field of radiology, where the disease can be diagnosed and assessed accurately for efficient decision making and planning of the treatment procedures.