Beyin Tümörü Varlığının Geleneksel Derin Öğrenme Tekniği Kullanılarak Tespiti ve MR Görüntülerinde K-Means Segmentasyonu Kullanılarak Kesin Tümör Konumlarının Belirlenmesi

Beyin dokusunda bulunan hücrelerin anormal bir şekilde büyümesi ile beyinde tümörler meydana gelmektedir. Beyinde bulunan tümörlerin büyük bir miktarı kanserli olduğu için, tümörlü beyin hasta kişinin ölümüne kadar sonuçlar doğurabilir. Beyin tümörlerinin görüntülenmesinde yaygın olarak MR görüntüleme araç olarak kullanılmaktadır. MR görüntüleri, görüntünün doku, karşıtlık, parlaklık ve sınır bilgilerini kullanarak hastalıklı bölgeler ile sağlıklı bölgeleri ayırabilmektedir. Bu sayede, beyin tümörünün şekli, konumu, büyüklüğü, alanı bulunarak hastalığın tedavi sürecinin planlaması yapılabilmektedir. Bu çalışmada, derin öğrenme yardımı ile MR görüntülerinde beyin tümörünün tespit edilmesi ve K-means ile bölütlenmesi işlemi yapılmaktadır. Çalışma sonucunda beyin tümörünün tespit edilmesinde elde edilen doğruluk oranı %84.45, hassasiyet %95.04 olarak bulunmuştur. Çalışma ile, tam otomatik bir beyin tümörü tespit etme ve bölütleme önerilerek, tümörlü bölgenin doğru bir şekilde çıkarılması amaçlanmıştır.

Anahtar Kelimeler:

manyetik rezonans görüntüleme, beyin tümör tanıma, beyin tümör bölütleme, derin öğrenme, k-means

Detection of the Brain Tumor Existance Using a Traditional Deep Learning Technique and Determination of Exact Tumor Locations Using K-Means Segmentation in MR Images

Tumors occur in the brain as the cells in the brain tissue grow abnormally. Since a large amount of tumors in the brain are cancerous, it can have consequences until the death of the sick person. MR imaging is widely used as a means of imaging brain tumors. MR images can distinguish diseased areas and healthy areas using the image's texture, contrast, brightness and boundary information. In this way, planning of the treatment process of the disease can be made by finding the shape, location, size and area of the brain tumor. In this study, the detection of the brain tumor in MR images by using deep learning and the segmentation with K-means are performed. As a result of the study, the accuracy obtained in detecting of the brain tumor is 84.45%, and the sensitivity is 95.04%. The study proposed detection and segmentation of the brain tumor and, extracting the tumor area automatically.

Keywords:

magnetic resonance imaging, brain tumor detection, brain tumor segmentation, deep learning, k-means,

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