Detecting intracranial haemorrhages in brain CT scans using deep learning techniques

Detecting intracranial haemorrhages in brain CT scans using deep learning techniques

Intracranial Haemorrhage(ICH) is a life-threatening emergency that requires quick diagnosis and treatment. A Computed Tomography (CT) Scan is taken of a patient when they arrive at a hospital, but an expert radiologist is required to accurately locate the haemorrhage in the scan. In this project, we...

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Bibliographic Details
Main Author: Vivek, Adrakatti
Other Authors: Jagath C Rajapakse
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Online Access:https://hdl.handle.net/10356/156755
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Institution: Nanyang Technological University
Language: English
Description
Summary:Intracranial Haemorrhage(ICH) is a life-threatening emergency that requires quick diagnosis and treatment. A Computed Tomography (CT) Scan is taken of a patient when they arrive at a hospital, but an expert radiologist is required to accurately locate the haemorrhage in the scan. In this project, we propose a novel algorithm for the detection and segmentation of the ICH in the Brain CT Scan Accurately. This will allow quick and accurate detection of ICH and assist doctors to take the necessary action. The algorithms have been implemented using Deep Learning Algorithms using PyTorch/Tensorflow libraries and using other libraries such as PyDicom and OpenCV.

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