Abstract: Researchers have been developing computerized methods to help the medical expert in their diagnostic process. Most of these efforts have primarily focused to improve the effectiveness in single patient data, like computing a brain lesion size, Cobb angle for scoliosis diagnosis etc. The comparison of multiple patients, their pathologies, for improving diagnosis has not received much attention.The patient to patient comparison should especially improve the diagnosis of diseases that affect large number of patients.The neurology department can greatly benefit from such multiple patient comparison due to the diagnosis of neurodegenerative diseases from one patient data has limitations. In this work, the search and retrieval mechanism is applied on Magnetic Resonance brain images to answer following questions:

  1. Is it possible to retrieve similar anatomical images from the large image database using the content of the images without using any keyword like patient id or name?
  2. Are we able to make clinical decision support system that predicts the disease class of the query image by retrieving the n images nearest to the query image from the large pool of images with the predicted disease class?

Work done

We have developed feature descriptors called Modified Local Binary Pattern (MOD_LBP) and Modified Local Ternary Pattern as a feature descriptor for the retrieval. Since the boundary of different levels (the height to which it belongs in the brain 3D volume) is not clearly defined, the degree of belongingness of the images in a particular level can be defined using some fuzzy membership functions. The local descriptor will be extended to Fuzzy local descriptor in order to extract more discriminate information from the images. The results can be improved by incorporating some visual semantics into the system in the form of reweighting the features or by using some classifiers like Neural Network, Support Vector Machine etc. The system can further be extended to support diagnosis process of some specific disease like dementia disorder, myelination problems etc.

(This is in collaboration with Dr B Kannan from CUSAT,  Mr.Manesh T from Prince Sattam Bin University, KSA and Dr. RejiRajan Varghese, Radioilogist from Cooperative medical college Cochin)