Automatic Segmentation of Acute Ischemic Stroke From DWI Using 3-D Fully Convolutional DenseNets

• Published in: IEEE transactions on medical imaging Vol. 37; no. 9; pp. 2149 - 2160
• Main Authors: Zhang, Rongzhao, Zhao, Lei, Lou, Wutao, Abrigo, Jill M., Mok, Vincent C. T., Chu, Winnie C. W., Wang, Defeng, Shi, Lin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D convolutional neural networks; Acute ischemic stroke segmentation; Aged; Aged, 80 and over; Aging; Algorithms; Artificial neural networks; Biomedical imaging; Brain - diagnostic imaging; Brain Ischemia - diagnostic imaging; Deep learning; Diagnosis; Diffusion Magnetic Resonance Imaging - methods; DWI; Female; Humans; Image processing; Image segmentation; Imaging, Three-Dimensional - methods; Information processing; Ischemia; Lesions; Localization; Male; Medical imaging; Middle Aged; Neural networks; Neural Networks (Computer); Objective function; Solid modeling; Stroke; Stroke - diagnostic imaging; Three-dimensional displays; Training; Two dimensional displays; Vascular diseases

Acute ischemic stroke is recognized as a common cerebral vascular disease in aging people. Accurate diagnosis and timely treatment can effectively improve the blood supply of the ischemic area and reduce the risk of disability or even death. Understanding the location and size of infarcts plays a cr...