Application of Textural Features to the Detection of Ocular Melanomas in Scintigraphy

• Published in: Computers and biomedical research Vol. 29; no. 5; pp. 418 - 428
• Main Authors: Colin, A., Bonafous, J., Boire, J.Y., Michelot, J., Bacin, F., Moreau, M.F., Veyre, A.
• Format: Journal Article
• Language: English
• Published: San Diego, CA Elsevier Inc 01.10.1996; Academic Press
• Subjects: Algorithms; Biological and medical sciences; Diagnosis, Computer-Assisted; Discriminant Analysis; Eye Neoplasms - diagnostic imaging; False Negative Reactions; Humans; Medical sciences; Melanoma - diagnostic imaging; Ophthalmology; Radionuclide Imaging - methods; Statistics, Nonparametric; Tumors and pseudotumors of the eye, orbit, eyelid, lacrimal apparatus; Radionuclide study; Performance evaluation; Human; Texture analysis; Segmentation; Image interpretation; Melanoma; Scintigraphy; Medical screening; Automated processing; Eye; Biomedical data processing; Eye disease; Tumor; Iodine
• ISSN: 0010-4809; 1090-2368
• DOI: 10.1006/cbmr.1996.0031

A method for automated detection of ocular melanoma in scintigraphic images is described. The algorithm first performs an automatic segmentation of the eyes on specific reference images. The images of the eyes are then analyzed using textural parameters computed in several directions and averaged to damp directional information. Assuming that only one eye per patient will be pathological, the ratio of the textural parameters of the two eyes is computed. A statistical analysis is performed over these ratios to select the most highly discriminating textural parameters and detect the pathological patients. The method has been tested successfully on a population of 23 individuals and we found significant differences between pathological and normal patients.