Fetal kafatası imgelerinin yarı-otomatik buluşsal bölütlenmesi

Yıl 2023, , 679 - 692, 07.10.2022

Umut Konur

https://doi.org/10.17341/gazimmfd.910514

Öz

Amaçları önceden tanımlanmış görevlerle ortaya konulan ve genellikle otomatik uygulamalar bağlamında anlamlı olan imge bölütleme problemi, ilgilenilen belli piksellerin çevrelerinden yalıtılmasını ele alır. İmgelerde çok ve ham durumda bulunarak artıklık, yararsızlık ve hatta görev-zorlaştırma barındıran verinin basitleştirilip, yalnız ilginç bölümleri içeren derlitoplu gösterimlerinin elde edilmesi ve bu bölümlerden tanımlayıcı özniteliklerin çıkarılması gerekir. Bu çalışmada, özel bir alanla ilgili olan ve ultrason görüntüleme ile edinilen enine-kesit fetal kafataslarını gösteren monokrom imgelerdeki kafatası çevritlerinin bulunması için kullanılan buluşsal bir yaklaşımdan söz edilmektedir. Bölütleme sürecinin başında, kullanıcının girdi imgedeki kafatası çevriti üstünde az sayıda noktayı elle işaretlemesi beklenmektedir. Çevritlerin parlak yoğunluklu piksellerden oluştuğu olgusundan ve görüntüleme teknolojisinden kaynaklanan bölütler arasında kopukluklar gözlenmesinden hareketle, açıklanan buluşsal bölütleme yöntemi, ortalama şekil modeli ve yoğunluğa-dayalı ortalama konum bulma kavramlarından yararlanmaktadır. Örnek imgelerdeki sonuçlar, hem görsel olarak hem de otomatik tanı sistemlerinde girdi olarak kullanıldığında, doyurucudur.

Anahtar Kelimeler

İmge bölütleme, ortalama şekil modeli, yoğunluğa-dayalı ortalama konum bulma, ultrason, enine-kesit

Semi-automatic heuristic segmentation of fetal skull images

Öz

The image segmentation problem, whose purposes are set by predefined tasks and which is generally significant in the context of automatic applications, deals with isolating image pixels that are of particular interest. Data; that are either redundant, useless or even task-complicating by being too much and raw, must be simplified, compact representations including only interesting portions must be obtained and descriptively useful features out of those must be extracted. In this work, a specific domain is considered and a heuristic approach for detecting skull contours in monochrome images acquired via the ultrasound technology displaying transcerebellar fetal skulls is described. At the start of the segmentation process, the user is expected to mark few points manually along the skull boundary on the input image. Knowing that skull contours are composed of pixels of high intensity and that discontinuities are observed between segments arising from the imaging technology, the described heuristic segmentation method utilizes the concepts of average shape model and intensity-based computation of average positions. The results for sample images, both visually and when they are used as inputs to automated diagnosis systems, are satisfactory.

Anahtar Kelimeler

Image segmentation, average shape model, intensity-based computation of average positions, ultrasound, transcerebellar

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