Abstract A 3-dimensional (3D) convolutional neural network is presented for the
segmentation and quantification of spontaneous intracerebral haemorrhage (ICH) in non …

A robust method is presented for the segmentation of the full cerebral vasculature in 4-
dimensional (4D) computed tomography (CT). The method consists of candidate vessel …

4D CT imaging has a great potential for use in stroke workup. A fully convolutional neural
network (CNN) for 3D multiclass segmentation in 4D CT is presented, which can be trained …

BACKGROUND AND PURPOSE: In the chronic phase after traumatic brain injury, DTI
findings reflect WM integrity. DTI interpretation in the subacute phase is less straightforward …

Efficient neural network training for 4D-CTA stroke imaging Page 1 Radboud Dissertation
Series Efficient neural network training for 4D-CTA stroke imaging Sil van de Leemput Page …

Computed Tomography (CT) is the first choice of imaging modality for different acute clinical
conditions28–30. CT is widely available and is a cheaper and faster imaging method with …

Vessel segmentation in medical imaging is the cornerstone of many applications. For
example, in acute ischemic stroke which is caused by a disturbance of blood supply to the …