:: Artikel Jurnal :: Kembali

Artikel Jurnal :: Kembali

Classification of digital mammogram based on nearest-neighbor method for breast cancer detection

Endah Purwanti, Soegianto Soelistiono (Faculty of Engineering, Universitas Indonesia, 2016)

 Abstrak

Breast cancer can be detected using digital mammograms. In this research study, a system is designed to classify digital mammograms into two classes, namely normal and abnormal, using the k-Nearest Neighbor (kNN) method. Prior to classification, the region of interest (ROI) of a mammogram is cropped, and the feature is extracted using the wavelet transformation method. Energy, mean, and standard deviation from wavelet decomposition coefficients are used as input for the classification. Optimal accuracy is obtained when wavelet decomposition level 3 is used with the feature combination of mean and standard deviation. The highest accuracy, sensitivity, and specificity of this method are 96.8%, 100%, and 95%, respectively.

 Metadata

No. Panggil : UI-IJTECH 7:1 (2016)
Entri utama-Nama orang :
Subjek :
Penerbitan : Depok: Faculty of Engineering, Universitas Indonesia, 2016
Sumber Pengatalogan : LibUI eng rda
ISSN : 20869614
Majalah/Jurnal : International Journal of Technology
Volume : Vol. 7, No. 1, January 2016: Hal. 71-77
Tipe Konten : text
Tipe Media : unmediated
Tipe Carrier : volume
Akses Elektronik : https://doi.org/10.14716/ijtech.v7i1.1393
Institusi Pemilik : Universitas Indonesia
Lokasi : Perpustakaan UI, Lantai 4 R. Koleksi Jurnal
  • Ketersediaan
  • Ulasan
No. Panggil No. Barkod Ketersediaan
UI-IJTECH 7:1 (2016) 08-23-39769125 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 9999920522140