A novel multistage CAD system for breast cancer diagnosis
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Computer-aided diagnosis (CAD) systems are widely used to diagnose breast cancer using mammography screening. In this research, we proposed a new multistage CAD system based on image decomposition with High-Dimensional Model Representation (HDMR) which is a divide-and-conquer algorithm. We used digital mammograms from Digital Database for Screening Mammography as dataset. We neglected BIRADS classification and used a brand-new clustering based on HDMR constant and breast size. To find the best performance of HDMR-based CAD system, we compared different pre-processing settings such as contrast enhancement with CLAHE and HDMR, feature extraction with HDMR, feature scaling, dimension reduction with Linear Discriminant Analysis. We used several Machine Learning algorithms and measured the performance of proposed system for normal-benign-malign classification, cancer detection, mass detection and found that the proposed system achieves 66%, 71% and 87% accuracy, respectively. We were able to achieve 92% accuracy, 100% sensitivity and 91% specificity in specific clusters. These results are comparable with deep learning-based methods although we simplified the pipeline and used brand-new HDMR-based processes.
Açıklama
Anahtar Kelimeler
Breast Cancer Diagnosis, Computer-Aided Diagnosis, Image Decomposition, Image Clustering, Contrast Enhancement, Hdmr
Kaynak
Signal Image and Video Processing
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
17
Sayı
5
