Impact of Diffusion–Perfusion Mismatch on Predicting Final Infarction Lesion Using Deep Learning
We report a study that validates the impact of diffusion-perfusion mismatch in a deep learning (DL) model predicting the final infarction lesion from baseline magnetic resonance imaging (MRI). From 472 consecutive patients with acute ischemic stroke, we gathered baseline and follow-up MRI having int...
Main Authors: | Sungdong Lee, Leonard Sunwoo, Youngwon Choi, Jae Hyup Jung, Seung Chai Jung, Joong-Ho Won |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9875295/ |
Similar Items
-
Endovascular Thrombectomy Versus Medical Therapy Alone in Patients With Large Core Based on Computed Tomography Perfusion
by: Amin N. Aghaebrahim, et al.
Published: (2021-11-01) -
Agreement between estimated computed tomography perfusion ischemic core and follow-up infarct on diffusion-weighted imaging
by: Wenjin Yang, et al.
Published: (2022-12-01) -
Impact of cardiac output and alveolar ventilation in estimating ventilation/perfusion mismatch in ARDS using electrical impedance tomography
by: Samuel Tuffet, et al.
Published: (2023-05-01) -
Optimal CT perfusion thresholds for core and penumbra in acute posterior circulation infarction
by: Leon Stephen Edwards, et al.
Published: (2023-02-01) -
Old laceration of deltoid muscle (case report)
by: V. V. Monastyrev, et al.
Published: (2015-11-01)