Automated segmentation of tissues using CT and MRI: a systematic review
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …
body using computed tomography and magnetic resonance imaging has been rapidly …
Intracerebral haemorrhage segmentation in non-contrast CT
Abstract A 3-dimensional (3D) convolutional neural network is presented for the
segmentation and quantification of spontaneous intracerebral haemorrhage (ICH) in non …
segmentation and quantification of spontaneous intracerebral haemorrhage (ICH) in non …
Image level training and prediction: intracranial hemorrhage identification in 3D non-contrast CT
Current hardware restrictions pose limitations on the use of convolutional neural networks
for medical image analysis. There is a large trade-off between network architecture and …
for medical image analysis. There is a large trade-off between network architecture and …
Determining ischemic stroke from CT-angiography imaging using symmetry-sensitive convolutional networks
Acute Ischemic Stroke (AIS) is the second leading cause of death worldwide in 2015, and 5
th in the United States. Neuro-imaging is routinely used in the diagnosis and management of …
th in the United States. Neuro-imaging is routinely used in the diagnosis and management of …
Robust segmentation of the full cerebral vasculature in 4D CT of suspected stroke patients
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 …
dimensional (4D) computed tomography (CT). The method consists of candidate vessel …
PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
Plasma cell segmentation is the first stage of a computer assisted automated diagnostic tool
for multiple myeloma (MM). Owing to large variability in biological cell types, a method for …
for multiple myeloma (MM). Owing to large variability in biological cell types, a method for …
Stacked bidirectional convolutional LSTMs for deriving 3D non-contrast CT from spatiotemporal 4D CT
The imaging workup in acute stroke can be simplified by deriving non-contrast CT (NCCT)
from CT perfusion (CTP) images. This results in reduced workup time and radiation dose. To …
from CT perfusion (CTP) images. This results in reduced workup time and radiation dose. To …
Multiclass brain tissue segmentation in 4D CT using convolutional neural networks
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 …
network (CNN) for 3D multiclass segmentation in 4D CT is presented, which can be trained …
Segmentation of spontaneous intracerebral hemorrhage on CT with a region growing method based on watershed preprocessing
Z Zhou, H Wan, H Zhang, X Chen, X Wang… - Frontiers in …, 2022 - frontiersin.org
Intracerebral hemorrhage (ICH) poses a great threat to human life due to its high incidence
and poor prognosis. Identification of the bleeding location and quantification of the volume …
and poor prognosis. Identification of the bleeding location and quantification of the volume …
Three-dimensional orbital wall modeling using paranasal sinus segmentation
Purpose Three-dimensional orbital wall modeling is a time-consuming process because of
the presence of pseudoforamina. We developed an automated three-dimensional modeling …
the presence of pseudoforamina. We developed an automated three-dimensional modeling …