Evaluation the sensitivity of diffusion and perfusion weighted imaging in therapeutic timing of stroke

Dayani, Mohammad Ali; Fatehi, Daryoush; Rostamzadeh, Omid; Rostamzadeh, Ayoob

doi:10.5958/0974-360x.2017.00342.0

Cited by 1 publication

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“…However, it has lower quality than MRI in terms of contrast (Zhao, Carass, Lee, He, & Prince, 2017). DW-MRI, on the other hand, is an imaging technique that identifies the stroke lesion type within minutes as it is based on the diffusion of water molecules (Dayani, Fatehi, Rostamzadeh, & Rostamzadeh, 2017). Among them, CT is the most preferred technique by specialists, especially for the detection of ischemic stroke.…”

Section: Specialists Use Medical Imaging Techniques Such As Magneticmentioning

confidence: 99%

Beyin Bilgisayarlı Tomografi Görüntülerinde Yapay Zeka Tabanlı Beyin Damar Hastalıkları Tespiti

KARATAŞ

Doğan

Kılıç

2022

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Cerebrovascular disease (CVD) causes paralysis and even mortality in humans due to blockage or bleeding of brain vessels. The early diagnosis of the CVD type by the specialist can avoid these casualties with a correct course of treatment. However, it is not always possible to recruit enough specialists in hospitals or emergency services. Therefore, in this study, an artificial intelligence (AI)-based clinical decision support system for CVD detection from brain computed tomography (CT) images is proposed to improve the diagnostic results and relieve the burden of specialists. The deep learning model, a subset of AI, was implemented through a two-step process in which CVD is first detected and then classified as ischemic or hemorrhagic. Moreover, the developed system is integrated into our custom-designed desktop application that offers a user-friendly interface for CVD diagnosis. Experimental results prove that our system has great potential to improve early diagnosis and treatment for specialists, which contributes to the recovery rate of patients.

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Section: Specialists Use Medical Imaging Techniques Such As Magneticmentioning

confidence: 99%

Beyin Bilgisayarlı Tomografi Görüntülerinde Yapay Zeka Tabanlı Beyin Damar Hastalıkları Tespiti

KARATAŞ

Doğan

Kılıç

2022

EJOSAT

View full text Add to dashboard Cite

show abstract

Evaluation the sensitivity of diffusion and perfusion weighted imaging in therapeutic timing of stroke

Cited by 1 publication

References 0 publications

Beyin Bilgisayarlı Tomografi Görüntülerinde Yapay Zeka Tabanlı Beyin Damar Hastalıkları Tespiti

Beyin Bilgisayarlı Tomografi Görüntülerinde Yapay Zeka Tabanlı Beyin Damar Hastalıkları Tespiti

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