Neural network based architecture for mammogram classification using genetic algorithm
| dc.contributor.guide | Robinson S | |
| dc.coverage.spatial | breast cancer Mammograms | |
| dc.creator.researcher | Valarmathi P | |
| dc.date.accessioned | 2019-01-15T05:27:48Z | |
| dc.date.available | 2019-01-15T05:27:48Z | |
| dc.date.awarded | 30/11/2017 | |
| dc.date.completed | 2017 | |
| dc.date.registered | 01/06/2014 | |
| dc.description.abstract | Each year around the world millions of women develop new cases of newlinebreast cancer Mammograms can be used to check for breast cancer in women newlinewho have no signs or symptoms of the disease Screening mammograms newlineusually involve two x ray pictures or images of each breast Screening newlinemammograms can also find Micro CalCifications MCCs a tiny deposits of newlinecalcium that sometimes indicate the presence of breast cancer newlineDiagnostic Mammogram can also be used to check for breast cancer newlineafter a lump or other sign or symptom of the disease. If calcifications are newlinegrouped together in a certain way it may be a sign of cancer If the MCCs newlinehave a suspicious look and pattern a biopsy will be recommended For newlineMCCs the interpretations of their presence are very difficult because of its newlinemorphological features The dense tissues especially in younger women may newlineeasily be misinterpreted as MCCs due to film emulsion error digitization newlineartefacts or anatomical structures such as fibrous strands breast borders or newlinehypertrophied lobules that almost similar to MCCs newline newline | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | None | |
| dc.format.dimensions | 23cm | |
| dc.format.extent | xvii, 133p. | |
| dc.identifier.uri | http://hdl.handle.net/10603/226175 | |
| dc.language | English | |
| dc.publisher.institution | Faculty of Information and Communication Engineering | |
| dc.publisher.place | Chennai | |
| dc.publisher.university | Anna University | |
| dc.relation | p.119-132 | |
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Engineering and Technology,Computer Science,Computer Science Theory and Methods | |
| dc.subject.keyword | Genetic Algorithm | |
| dc.subject.keyword | Mammogram | |
| dc.subject.keyword | Neural Network | |
| dc.title | Neural network based architecture for mammogram classification using genetic algorithm | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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