Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156755
Title: Detecting intracranial haemorrhages in brain CT scans using deep learning techniques
Authors: Vivek, Adrakatti
Keywords: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Vivek, A. (2022). Detecting intracranial haemorrhages in brain CT scans using deep learning techniques. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156755
Project: SCSE21-0211
Abstract: 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.
URI: https://hdl.handle.net/10356/156755
Fulltext Permission: embargo_restricted_20240421
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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  Until 2024-04-21
6.22 MBAdobe PDFUnder embargo until Apr 21, 2024

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