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Cerebral Ventricles

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Deep Learning-based Approach for Brainstem and Ventricular MR Planimetry: Application in Patients with Progressive Supranuclear Palsy.

Radiology. Artificial intelligence
Purpose To develop a fast and fully automated deep learning (DL)-based method for the MRI planimetric segmentation and measurement of the brainstem and ventricular structures most affected in patients with progressive supranuclear palsy (PSP). Materi...

Robot-guided Ventriculoperitoneal Shunt in Slit-like Ventricles.

Neurology India
BACKGROUND: Ventriculoperitoneal shunt (VPS) is the most common procedure used in the management of hydrocephalus regardless of the etiology. The standard free-hand technique is used for the placement of VPS in patients with enlarged ventricles. In p...

Comparison of morphometric parameters in prediction of hydrocephalus using random forests.

Computers in biology and medicine
Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hy...

Fully automated intracranial ventricle segmentation on CT with 2D regional convolutional neural network to estimate ventricular volume.

International journal of computer assisted radiology and surgery
PURPOSE: Hydrocephalus is a clinically significant condition which can have devastating consequences if left untreated. Currently available methods for quantifying this condition using CT imaging are unreliable and prone to error. The purpose of this...

Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly.

NeuroImage. Clinical
Numerous brain disorders are associated with ventriculomegaly, including both neuro-degenerative diseases and cerebrospinal fluid disorders. Detailed evaluation of the ventricular system is important for these conditions to help understand the pathog...

Automatically measuring brain ventricular volume within PACS using artificial intelligence.

PloS one
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and...

Learning and combining image neighborhoods using random forests for neonatal brain disease classification.

Medical image analysis
It is challenging to characterize and classify normal and abnormal brain development during early childhood. To reduce the complexity of heterogeneous data population, manifold learning techniques are increasingly applied, which find a low-dimensiona...