Scopus
YÖKSİS Eşleşti
Adrenal tumor segmentation method for MR images
Computer Methods and Programs in Biomedicine · Ekim 2018
YÖKSİS Kayıtları
Adrenal tumor segmentation method for MR images
Elsevier BV · 2018 SCI-Expanded
PROFESÖR MUSTAFA KOPLAY →
Makale Bilgileri
DergiComputer Methods and Programs in Biomedicine
Yayın TarihiEkim 2018
Cilt / Sayfa164 · 87-100
Scopus ID2-s2.0-85050272714
Özet
Background and objective: Adrenal tumors, which occur on adrenal glands, are incidentally determined. The liver, spleen, spinal cord, and kidney surround the adrenal glands. Therefore, tumors on the adrenal glands can be adherent to other organs. This is a problem in adrenal tumor segmentation. In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation. Methods: This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems. The proposed hybrid method incorporates many image processing methods, which include active contour, adaptive thresholding, contrast limited adaptive histogram equalization (CLAHE), image erosion, and region growing. Results: The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven metrics: sensitivity, specificity, accuracy, precision, Dice Coefficient, Jaccard Rate, and structural similarity index (SSIM). The proposed method eliminates some of the discussed problems with success rates of 74.84%, 99.99%, 99.84%, 93.49%, 82.09%, 71.24%, 99.48% for the metrics, respectively. Conclusions: This study presents a new method for adrenal tumor segmentation, and avoids some of the problems preventing accurate segmentation, especially for cyst-based tumors.
Yazarlar (5)
1
Mücahid Barstuğan
ORCID: 0000-0001-9790-5890
2
Rahime Ceylan
ORCID: 0000-0003-0294-5692
3
Semih Asoğlu
4
Hakan Cebeci
5
M. Koplay
ORCID: 0000-0001-7513-4968
Anahtar Kelimeler
Adrenal tumor segmentation
CAD system
Hybrid approach
MR images
Kurumlar
Konya Technical University
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
10
Atıf
5
Yazar
4
Anahtar Kelime