Intelligent Shape Feature Extraction and Indexing for Efficient Content-Based Medical Image Retrieval

Abstract

We detail the process of creating an efficient and innovative system for retrieving medical images based on their content, one
that can extract and index crucial information like the morphology of regions. We begin with a review of the system’s architecture
and its primary parts. We have investigated a quick active contour method based on the geometric heat differential equation
for grayscale segmentation to detect areas. A collection of shape-based characteristics is used for region representation. We
use a method for organizing features using -dimensional feature vectors. In order to get images, the procedure compares query
vectors to indexed feature vectors for similarity. We arrange the feature index using a convex hull model that uses the heat differential
equation to decrease the search space. Certain parts of our strategy have been tested and validated via the execution of
experiments. Lastly, the computational complexity of the system, along with its benefits and drawbacks, are examined.