Automatic Sub Classification of Benign Breast Tumor

Autor:	Manish Joshi, Aparna Bhale
Rok vydání:	2017
Předmět:	medicine.medical_specialty business.industry Feature extraction medicine.disease Sub classification Breast tumor Benign breast tumors Benign tumor Support vector machine Mammographic image Medicine Medical history Radiology business
Zdroj:	Lecture Notes in Networks and Systems ISBN: 9789811069154
DOI:	10.1007/978-981-10-6916-1_20
Popis:	This paper describes about automatic classification of benign lesions. Our re-search work mostly aims at development of a data driven effective classification system to determine type of benign breast tumors. The existing system in medical field identifies the type of benign breast tumor based on histopathological report obtained after a painful surgical process. Our target is to develop a system that would work without histopathological attributes to avoid pains to the patient. Our focus was to eliminate the role of histopathological attributes in the detection of benign tumor type. So we tried to identify correlation of histopathological features with mammographic image features and patient history features in order to explore if histopathological features can be replaced by corresponding correlated features. With replaced attributes we gain training accuracy for J48 as 79.78% and with SVM 81.91%. We obtained testing accuracy for J48 and SVM as 100% and 90.90% respectively.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::361901eaff43c3208ec18783873c2394 https://doi.org/10.1007/978-981-10-6916-1_20 Zobrazit plný text záznamu