Vasküler Görüntüleyici Sistem

Year 2021, , 1 - 17, 15.06.2021

Turgut Gökbulut Burak Ünal Burhan Kazi Onur Özdal Mengi

https://doi.org/10.31466/kfbd.744104

Abstract

Günümüzde hızla gelişen kızılötesi görüntüleme teknolojisi tıp dünyasında yoğun olarak kullanılmaktadır. Kandaki alyuvarlarda bulunan hemoglobin kızılötesi ışınları emebilmektedir. Bu sayede damarlar diğer dokulara göre daha koyu ve belirgin bir şekilde görünür. Damar görüntüsü elde etmek için kullanılan cihazlar oldukça pahalıdır. Bunun sebebi bu cihazlarda yüksek hassasiyette ve yoğunlukta kızılötesi görüntü alan CCD sensörlü kameraların kullanılmasıdır. Bu sebeple maliyeti düşürmek için çok pahalı CCD sensör yerine fiyatı çok daha uygun olan CMOS sensörlü kızılötesi kameralar kullanılabilir. Ancak CMOS sensörü kullanan kameralardan elde edilen görüntü CCD sensörü kullanan kameralardan elde edilen görüntü kadar iyi değildir. Bu sebeple daha iyi görüntü elde etmek için gelişmiş görüntü işleme tekniklerine ihtiyaç vardır. 850nm kızılötesi ışık, CMOS sensörlü kamera ve 850nm dalga boyuna sahip bant geçiren fitre kullanılarak cildin 3mm derinliğindeki damar görüntüsü elde edilir. Elde edilen görüntü Raspberry Pi mikroişlemcisi kullanılarak OpenCV açık kaynak kodlu kütüphanesi yardımıyla Python dilinde sırasıyla; gri seviyeye dönüştürme, el maskesi için binari metot, damar maskeleme için ise medyan filtre ve canny metot kullanılmıştır. Ayrıca elde edilen görüntüyü iyileştirmek için çeşitli morfolojik işlemler (aşındırma ve genişletme) kullanılmıştır.

Keywords

CMOS, Python, Raspberry Pi, Medyan Filtre, Canny, Binari

Vascular Viewer System

Abstract

Rapidly developing infrared imaging technology is used extensively in the medical world. The hemoglobin contained in the red blood cells in the blood can absorb infrared rays. In this way, the vessels appear darker and more pronounced than other tissues. The devices used to obtain a vascular image are quite expensive. The reason for this is the use of CCD sensor cameras with high sensitivity and intensity infrared images in these devices. For this reason, in order to reduce the cost, infrared cameras with CMOS sensors, which are much more affordable, can be used instead of the very expensive CCD sensor. However, the image obtained from cameras using CMOS sensors is not as good as the image obtained from cameras using CCD sensors. Therefore, advanced image processing techniques are needed to obtain better images. Using the 850nm infrared light, a camera with CMOS sensor and a bandpass filter with 850nm wavelength, a 3mm deep vein image of the skin is obtained. The obtained image is in Python language, respectively, with the help of OpenCV open source library using Raspberry Pi microprocessor; conversion to gray level, binary method for hand mask, median filter and canny method are used for vein masking. In addition, various morphological processes (erode and dilated) were used to improve the image obtained.

Keywords

CMOS, Python, Raspberry Pi, Median filter, Canny, Binary

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