International Journal of Applied Mathematics Electronics and Computers

2147-8228 2147-8228

PLUSBASE AKADEMİ ORGANİZASYON VE DANIŞMANLIK

10.18100/ijamec.679142

Engineering

Mühendislik

Detection of Breast Region of Interest via Breast MR Scan on an Axial Slice

https://orcid.org/0000-0002-1999-2797

Çetinel

Gökçen

SAKARYA UNIV

https://orcid.org/0000-0001-7761-2417

Mutlu

Fuldem

SAKARYA ÜNİVERSİTESİ, TIP FAKÜLTESİ, DAHİLİ TIP BİLİMLERİ BÖLÜMÜ, RADYOLOJİ ANABİLİM DALI

https://orcid.org/0000-0002-7040-7952

Gül

Sevda

SAKARYA UNIVERSITY, SAKARYA VOCATIONAL SCHOOL

06 30 2020

8 2 39 44 01 23 2020 04 29 2020

2013

International Journal of Applied Mathematics Electronics and Computers

Breast cancer is one of the most common cancer types especially met in women. The number of breast cancer patients increases every year. Thus, to detect breast cancer at its early stages gains importance. Breast region detection is the pioneering step of breast cancer diagnosis researches performed via image processing techniques. The performance of computer-aided breast cancer diagnosis systems can be improved by exactly determining the breast region of interest. In this study, the goal is to determine a region of interest for breast MR images, in which one or more lesion can appear. The achieved region includes two breasts and lymph nodes. The proposed region of interest detection system is fully automatic and it utilizes several image processing techniques. At first, the local adaptive thresholding technique is applied to the noise-filtered grey level breast magnetic resonance images taken with ethical permissions from Sakarya Education and Research Hospital. After adaptive thresholding, connected component analysis is performed to exclude extra structures around the breast region as thorax area. This analysis selects the largest area in the binary image which corresponds to a gyrate region including breast area and lymph nodes over the backbone. Then, the integral of horizontal projection is calculated to determine an optimum horizontal line that allows setting the region of interest apart. In the following step, sternum midpoint is detected to separate the right breast from the left one. Finally, a masking operation is applied to get corresponding right and left breast regions in the original MR image. To evaluate the performance of the proposed study, the results of automatic region of interest detection system are compared with the manual region of interest selection performed by an expert radiologist. Dice similarity coefficient and Jaccard coefficient are used as performance criteria. According to the results, the proposed system can detect region of interest for computer-aided breast cancer diagnosis researches, exactly.

Breast cancer Region of interest Magnetic resonance imaging Local adaptive thresholding Connected component analysis

TÜBİTAK

118E201

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