Affiliation:
1. North-Eastern Hill University, India
Abstract
Content-based image retrieval is a promising technique to access visual data. With the huge development of computer storage, networking, and the transmission technology now it becomes possible to retrieve the image data beside the text. In the traditional way, we find the content of image by the tagged image with some indexed text. With the development of machine learning technique in the domain of artificial intelligence, the feature extraction techniques become easier for CBIR. The medical images are continuously increasing day by day where each image holds some specific and unique information about some specific disease. The objectives of using CBIR in medical diagnosis are to provide correct and effective information to the specialist for the quality and efficient diagnosis of the disease. Medical image content requires different types of CBIR technique for different medical image acquisition techniques such as MRI, CT, PET Scan, USG, MRS, etc. So, in this concern, each CBIR technique has its unique feature extraction algorithm for each acquisition technique.
Reference32 articles.
1. Content-based image retrieval using color and shape features. International Journal of Advanced Research in Electrical;R.Chaudhari;Electronics and Instrumentation Engineering,2012
2. ChenY.LiJ.WangJ. Z. (2006). Machine learning and statistical modeling approaches to image retrieval (Vol. 14). Springer Science & Business Media.
3. Image retrieval
4. Pattern-Based Image Retrieval System built with Object Tracking and Segmentation Concepts.;T.Dharani;International Journal of Computer & Mathematical Sciences,2017
5. Dharani, T., & Laurence Aroquiaraj, I. (2017). An Essential Image Augmentation Processes for Pattern Based Image Retrieval System. Academic Press.