Vol. 3 Issue 1
Year: 2016
Issue:Jan-Mar
Title:Cuckoo Search Framework For Feature Selection And Classifier Optimization In Compressed Medical Image Retrieval
Author Name:Reddi Kiran Kumar and Vamsidhar Enireddy
Synopsis:
With the availability of different medical imaging equipment for diagnoses, medical professionals are increasingly depending on the computer aided techniques for retrieving similar images from large repositories. This work investigates medical image retrieval problem for lossless compressed images. Lossless compression technique is utilized for compressing the medical images for easy transmission and storage. Texture features are extracted using Gabor filters, Shape features using the Gabor - shape and best features of these are selected by using a novel Cuckoo Search algorithm and compared with other statistical techniques. Classification was done by using the Recurrent neural Network. Optimization of the neural network is done using the Cuckoo Search. Experimental results show the advantages of the proposed framework.
Year: 2016
Issue:Jan-Mar
Title:Cuckoo Search Framework For Feature Selection And Classifier Optimization In Compressed Medical Image Retrieval
Author Name:Reddi Kiran Kumar and Vamsidhar Enireddy
Synopsis:
With the availability of different medical imaging equipment for diagnoses, medical professionals are increasingly depending on the computer aided techniques for retrieving similar images from large repositories. This work investigates medical image retrieval problem for lossless compressed images. Lossless compression technique is utilized for compressing the medical images for easy transmission and storage. Texture features are extracted using Gabor filters, Shape features using the Gabor - shape and best features of these are selected by using a novel Cuckoo Search algorithm and compared with other statistical techniques. Classification was done by using the Recurrent neural Network. Optimization of the neural network is done using the Cuckoo Search. Experimental results show the advantages of the proposed framework.
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