Abstract
Computed Tomography (CT) images are cross-sectional images of any specific area of a human body which allows doctors to see inside of a patient. CT scan is almost always the first imaging modality used to assess patients with suspected hemorrhage. A CT scan provides image reports in the form of grey shades. It is sometimes difficult to distinguish between two areas because the shades of grey in a CT image are occasionally similar. CT scan (Particularly “Non-Contrast Head CT Scan”) is the current guideline for primary imaging of patients with any head injuries or brain stroke like symptoms. To obtain any findings from the CT image, Radiologists or other doctors need to examine the images. Deep-learning is an important tool used in radiology and medical imaging which provides a better understanding of the image with more efficiency and quicker exam time. The main idea of this project is developing a model using classification algorithms which can be used to classify or detect hemorrhage in a CT image. The dataset consists of both normal CTs and CTs with hemorrhage. Deep learning is used to develop a model that can detect whether a CT image shows a hemorrhage or not.
Highlights
Traumatic head injuries from events such as accidents or falls might result in sudden hemorrhaging in the brain
We developed a Convolutional Neural Network (CNN) model to classify Computed Tomography (CT) scan images based on its features
4.4 CNN architecture The following Figure 9 represents the CNN layers used in this model
Summary
Traumatic head injuries from events such as accidents or falls might result in sudden hemorrhaging in the brain. To evaluate a subject with a head injury, CT (Computed Tomography) Scan is the primary diagnostic tool used as it can generate reports rapidly. Windowing method is generally used to display CT scans which transform the HU values (Hounsfield Unit) into grayscale values ([0, 255]). We have different window parameters and each parameter can be used to display different features of the brain tissues in a CT image. To interpret a CT image or to determine if a hemorrhage has occurred, we need an experienced radiologist. This diagnosis process highly depends on the availability of a specialiJOE ‒ Vol 17, No 01, 2021
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