Open AccessAnalyzing and detecting hemorrhagic and ischemic strokebased on bit plane slicing and edge detection algorithms
Author(s) -
Warqaa Shaher AlAzawee,
Zobeda H. Naji,
Weaam Talaat Ali
Publication year - 2022
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v25.i2.pp1003-1010
Subject(s) - computer science , canny edge detector , algorithm , enhanced data rates for gsm evolution , artificial intelligence , edge detection , process (computing) , transformation (genetics) , cad , computer vision , image (mathematics) , image processing , engineering , biochemistry , chemistry , engineering drawing , gene , operating system
Nowadays, in the medical world, analyzing and diagnosing acute brain stroke and its location is a difficult process. In many hospitals, however, striking symptoms with the use of computed tomography (CT) imaging for patients is an important step in screening and diagnosis. Furthermore, computer-assisted accurate detection of diseased brain regions Because of the several sorts of strokes, their uneven form, and their great intensity and size, aided design is extremely challenging. Using the bit plan slice technique and the canny detector, we created and suggested a novel approach. Our algorithm produces excellent outcomes. The results demonstrate that our proposed algorithm is an accurate and reliable technique. This study also indicates that this system can detect two different types of strokes: hemorrhagic and ischemic strokes. The results of a comparison study of our suggested technique and other methods such as negative and logarithmic transformation methods are also included in this article.