Identification of acute intracranial bleed on computed tomography using computer aided detection

Abstract

Intracranial haemorrhage can be life threatening. Timely detection of acute intracranial haemorrhage in an emergency room is essential so that the patient can be given medical attention without delay. This has led to the use of Computer Aided Detection (CAD) systems which can help to pick up and prioritize patients with high risk of bleeding. A CAD for identification of acute intracranial haemorrhage in Computed Tomography (CT) on a per patient basis was developed in this project. The CAD is aimed to be a triage tool which determines the priority of image being read by radiologists. It was developed and validated using 119 and 108 volumes of brain CT images respectively. The volumes were first registered to standard Montreal Neurological Institute (MNI) space. Slices close to the base and top of the skull that tend to contribute to false positives were omitted. Then, the volumes were analysed by a fully automated CAD program developed in MATLAB. The algorithm involved multiple thresholding and symmetry detection in 3D to detect acute intracranial haemorrhage. The evaluation took around 5s per volume. On a per patient basis, the CAD achieved sensitivity of 75.0%, specificity of 83.8%, and accuracy of 80.6% in the validation set.