eprintid: 19190
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/91/90
datestamp: 2024-06-04 14:11:38
lastmod: 2024-06-04 14:11:38
status_changed: 2024-06-04 14:05:07
type: conference_item
metadata_visibility: show
creators_name: Memon, K.
creators_name: Yahya, N.
creators_name: Yusoff, M.Z.
creators_name: Hashim, H.
creators_name: Ali, S.S.A.
creators_name: Siddiqui, S.
title: Image Pre-processing for Differential Diagnosis of Multiple Sclerosis using Brain MRI
ispublished: pub
keywords: Extraction; Magnetic resonance imaging; Medical imaging; Semantic Segmentation; Semantics, Brain MRI; Computer-aided; Deeplabv3; Differential diagnosis; Image preprocessing; Lesion segmentations; Multiple sclerosis; Neurological disorders; Neuromyelitis optica; Skull stripping, Computer aided diagnosis
note: cited By 1; Conference of 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023 ; Conference Date: 5 May 2023 Through 6 May 2023; Conference Code:190031
abstract: Multiple sclerosis (MS) is a type of auto-immune disease affecting the human brain. One of the challenges in clinical diagnosis of MS lies in its close similarity to another type of brain auto-immune disease known as neuromyelitis optica (MNO). Hence, various researchers are looking into the development of computer-aided differential diagnosis (CADD) of MS vs. MNO. Generally, the development of the CADD, involves image pre-processing, feature extraction, statistical analysis and training and testing of the classification model. The focus of this paper is on the 2 critical pre-processing steps prior to classification of MS vs. MNO, namely skull stripping and lesion segmentation. In particular, both skull stripping and brain lesion segmentation are tested with a popular semantic segmentation technique, DeepLabV3. For comparison, a recently published technique, SynthStrip from FreeSurfer 1, developed by Harvard University is also tested for brain extraction / skull removal. Similarly for segmentation of brain lesions, Lesion Segmentation Tool in SPM Toolbox is tested and compared. The results from this study provides insight on what are the appropriate pre-processing techniques for the development of an reliable automatic differential diagnosis tool for multiple sclerosis conditions. © 2023 IEEE.
date: 2023
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165540084&doi=10.1109%2fViTECoN58111.2023.10157177&partnerID=40&md5=863911fa4df8cc4a4157ad4592ea2650
id_number: 10.1109/ViTECoN58111.2023.10157177
full_text_status: none
publication: ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings
refereed: TRUE
citation:   Memon, K. and Yahya, N. and Yusoff, M.Z. and Hashim, H. and Ali, S.S.A. and Siddiqui, S.  (2023) Image Pre-processing for Differential Diagnosis of Multiple Sclerosis using Brain MRI.  In: UNSPECIFIED.