Title :
Texture analysis for classification of cervix lesions
Author :
Ji, Qiang ; Engel, John ; Craine, Eric
Author_Institution :
Dept. of Comput. Sci., Nevada Univ., Reno, NV, USA
Abstract :
This paper presents a generalized statistical texture analysis technique for characterizing and recognizing typical, diagnostically most important, vascular patterns relating to cervical lesions from colposcopic images. The contributions of the research include: (1) the introduction of a generalized texture analysis technique based on the combination of the conventional statistical and structural textural analysis approaches by using a statistical description of geometric primitives; (2) the introduction of a set of textural measures that capture the specific characteristics of cervical textures as perceived by humans. An experimental study with real images demonstrated the feasibility and promise of the proposed approach in discriminating between cervical texture patterns indicative of different stages of cervical lesions.
Keywords :
cancer; gynaecology; image classification; image texture; medical image processing; optical images; statistical analysis; cervix lesions classification; colposcopic images; geometric primitives; lesion stage; medical diagnostic imaging; texture analysis; typical diagnostically most important vascular patterns; Character recognition; Humans; Image analysis; Image recognition; Image texture analysis; Lesions; Pathology; Pattern analysis; Pattern recognition; Testing; Female; Humans; Uterine Cervical Neoplasms;
Journal_Title :
Medical Imaging, IEEE Transactions on