Survey on Machine and Deep Learning Methods used in CT Scan Brain Diseases Diagnosis

What is it about?

A CT scan of the brain is the first option for diagnosing intracranial disease. However, as the number of patients increases, there is a shortage of doctors who can make a diagnosis. In recent years, many computer-aided diagnostic algorithms have been developed to assist physicians in diagnosing and saving time. Computed Tomography (CT) is the most widely used diagnostic imaging method for diagnosing brain disorders due to its speed, cost-effectiveness, and wide range of applications. However, because of the brain's complex structure, finding bleeding points and lesions is difficult, and doctors have a difficult time diagnosing the disease quickly and accurately. This article gives an overview of recent machine learning and deep learning methods for detecting and classifying brain diseases from CT images.

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Photo by National Cancer Institute on Unsplash

Photo by National Cancer Institute on Unsplash

Why is it important?

This paper provides some key insights into recent ML/DL technologies in the medical field, which are now being used in brain disorder research. Identification, feature extraction, and classification methods in the fields of ML and DL have become more advanced over time.