dc.contributor.author | Ucan, Osman N. | |
dc.contributor.author | Gorgel, Pelin | |
dc.contributor.author | Sertbas, Ahmet | |
dc.date.accessioned | 2021-03-03T13:49:05Z | |
dc.date.available | 2021-03-03T13:49:05Z | |
dc.identifier.citation | Gorgel P., Sertbas A., Ucan O. N. , "A Fuzzy Inference System Combined with Wavelet Transform for Breast Mass Classification", 35th International Conference on Telecommunications and Signal Processing (TSP), Prague, Çek Cumhuriyeti, 3 - 04 Temmuz 2012, ss.644-647 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.other | av_362f8550-8d05-45fc-a932-14f66a4b11bf | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/40598 | |
dc.identifier.uri | https://doi.org/10.1109/tsp.2012.6256376 | |
dc.description.abstract | This paper proposes a combination of the Fast Wavelet Transform (FWT) and Adaptive Neuro-fuzzy Inference System (ANFIS) methods. The goal is classification of breast masses as benign or malignant by applying this method consecutively to the extracted features of the Region of Interests (ROIs). This study is developed to decrease the number of the missing cancerous regions or unnecessary biopsies. The neurofuzzy subtractive clustering classification method achieved a classification accuracy of 85% without using FWT multiresolution analysis and 92% with FWT. The satisfying results demonstrate that the developed system could help the radiologists for a true diagnosis. | |
dc.language.iso | eng | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği | |
dc.subject | Sinyal İşleme | |
dc.subject | TELEKOMÜNİKASYON | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | Mühendislik | |
dc.subject | MÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK | |
dc.title | A Fuzzy Inference System Combined with Wavelet Transform for Breast Mass Classification | |
dc.type | Bildiri | |
dc.contributor.department | Aydın Adnan Menderes Üniversitesi , , | |
dc.contributor.firstauthorID | 139043 | |