Medical Image Retrieval Using Efficient Texture and Color Patterns with Neural Network Classifier

  • C. Ashok KumarEmail author
  • S. Sathiamoorthy
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 49)


Presently, the usage of medicinal images has drastically increased and it provides extensive details related to the patient’s health status. It shows the applicability of diagnosing the disease and stored in a memory for examination purposes. For the retrieval of medical images in a real world environment, significant need is present in the designing of an effective medical image indexing and retrieval technique. This paper offers an efficient medical image retrieval (MIR) model through feature extraction based classification model. Here, Directional local ternary quantized extrema patterns (DLTerQEPs) and autocorrelogram (AC) based feature extraction process takes place to extract texture and color features. Next, neural network (NN) based classification process takes place. The investigation of the simulation results takes place to showcase the betterment of the presented mode. During experimentation process, it is noticed that the presented model is superior to compared methods.


Classifier Image retrieval Medical images Deep learning 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceAnnamalai UniversityChidambaramIndia
  2. 2.Tamil Virtual AcademyChennaiIndia

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