Development of a Nonlinear K-Law Spectral Signature Index to Classify Basophilic Inclusion Bodies of the White Spot Syndrome Virus

In this paper a novel technique is developed to classify White Spot Syndrome Virus (WSSV) inclusion bodies found in shrimp tissues by the analysis of digitalized images from infected samples. Since the early 90’s, WSSV has been affecting the economy of shrimp producers around the world restraining aquaculture production. Once the clinical signs are developed; mortality can reach 100% in 3 days. Several techniques have been implemented and developed for viral and bacterial diagnostics from penaeid shrimps; however histology is still considered the common tool in medical and veterinary diagnostics tasks. WSSV slide images were acquired by a computational image capture system and a new spectral signature index is developed to obtain a quantitative measurement of the complexity pattern found in WSSV inclusion bodies. Representative groups of WSSV inclusion bodies from infected shrimp tissues and organs were analyzed. The results show that inclusion bodies analyzed are well defined in a clear numerical fringe, obtained by the calculation by this spectral signature index.