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Cervix Cancer Classification using Colposcopy Images by Deep Learning Method
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vasudha Mittal, Ajay Juneja, Mamta |
| Copyright Year | 2018 |
| Abstract | Cervix cancer is one of the trivial form of cancer in women at present. In the world, it is one of the major reasons for womens' death. Due to cervix cancer, most of the deaths are happening in less defoliated areas of the world. Death rate due cervix cancer can be reduced if it would be detected at early stages. Since, cervix cancer has no symptoms so regular checkup is needed for its diagnosis. Colposcopy images are the images of woman\'s cervix taken using a special microscope called colposcope after application of acetic acid on cervix. Colposcopy is a procedure which is used to check precancerous and abnormal areas in the cervix so that normal and cancerous tissues can be classified. So, we are using colposcopy images dataset for our task to classify them in normal and cancerous images. In our work, a deep learning convolutional neural network (CNN) is applied on colposcopy images of cervix for classification. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ijetsr.com/images/short_pdf/1521291043_426-432-chd1028_word_etsr.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
