Cascaded classifiers and stacking methods for classification of pulmonary nodule characteristics

KAYA, AYDIN

doi:10.1016/j.cmpb.2018.10.009

Cascaded classifiers and stacking methods for classification of pulmonary nodule characteristics

Atıf İçin Kopyala

KAYA A.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, cilt.166, ss.77-89, 2018 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 166
Basım Tarihi: 2018
Doi Numarası: 10.1016/j.cmpb.2018.10.009
Dergi Adı: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.77-89
Hacettepe Üniversitesi Adresli: Evet

Özet

Background and Objectives: Detection and classification of pulmonary nodules are critical tasks in medical image analysis. The Lung Image Database Consortium (LIDC) database is a widely used resource for small pulmonary nodule classification research. This dataset is comprised of nodule characteristic evaluations and CT scans of patients. Although these characteristics are utilized in several studies, they can be used to improve classification performance.