B. Vijayakumari, G. Ulaganathan, A. Banumathi, A. Banu, M. Kayalvizhi
{"title":"Dental cyst diagnosis using texture analysis","authors":"B. Vijayakumari, G. Ulaganathan, A. Banumathi, A. Banu, M. Kayalvizhi","doi":"10.1109/MVIP.2012.6428774","DOIUrl":null,"url":null,"abstract":"Dental or oral cysts are fairly a common occurrence in the mouth. There are several common types of dental cysts like periapical cyst, keratocyst, primordial and dentigerous cysts. The most common treatment for cysts is removal of the cyst region. Differentiating odontogenic keratocysts and ameloblastomas from other cystic lesions in the maxillomandibular region is important because of their high recurrence rates. Conventional radiography, CT, and fine-needle aspiration biopsy are limited for differential diagnosis. To assist this process for the dentist, this work focuses an automatic analysis of cyst using the texture information. This work involves three sections. The first section is performance analysis of preprocessing for various cysts images. The second section is extracting gray level co-occurrence matrix for all the cyst patterns. Analyzing different cyst pattern using the texture properties is the third section.","PeriodicalId":170271,"journal":{"name":"2012 International Conference on Machine Vision and Image Processing (MVIP)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVIP.2012.6428774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Dental or oral cysts are fairly a common occurrence in the mouth. There are several common types of dental cysts like periapical cyst, keratocyst, primordial and dentigerous cysts. The most common treatment for cysts is removal of the cyst region. Differentiating odontogenic keratocysts and ameloblastomas from other cystic lesions in the maxillomandibular region is important because of their high recurrence rates. Conventional radiography, CT, and fine-needle aspiration biopsy are limited for differential diagnosis. To assist this process for the dentist, this work focuses an automatic analysis of cyst using the texture information. This work involves three sections. The first section is performance analysis of preprocessing for various cysts images. The second section is extracting gray level co-occurrence matrix for all the cyst patterns. Analyzing different cyst pattern using the texture properties is the third section.