PItcHPERFeCT: Primary Intracranial Hemorrhage Probability Estimation using Random Forests on CT.

ABSTRACT:

Introduction

Intracerebral hemorrhage (ICH), where a blood vessel ruptures into areas of the brain, accounts for approximately 10-15% of all strokes. X-ray computed tomography (CT) scanning is largely used to assess the location and volume of these hemorrhages. Manual segmentation of the CT scan using planimetry by an expert reader is the gold standard for volume estimation, but is time-consuming and has within- and across-reader variability. We propose a fully automated segmentation approach using a random forest algorithm with features extracted from X-ray computed tomography (CT) scans.

Methods

The Minimally Invasive Surgery plus rt-PA in ICH Evacuation (MISTIE) trial was a multi-site Phase II clinical trial that tested the safety of hemorrhage removal using recombinant-t

SUBMITTER: Muschelli J 

PROVIDER: S-EPMC5328741 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature