Nakagami imaging and morphing for multiple sclerosis lesion volume estimation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00179906%3A_____%2F24%3A10469462" target="_blank" >RIV/00179906:_____/24:10469462 - isvavai.cz</a>

Alternative codes found

RIV/62690094:18450/24:50020617

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=6qvDdRfWAo" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=6qvDdRfWAo</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2023.121250" target="_blank" >10.1016/j.eswa.2023.121250</a>

Result language

angličtina

Original language name

Nakagami imaging and morphing for multiple sclerosis lesion volume estimation

Original language description

Monitoring and tracking the size and the number of multiple sclerosis (MS) lesions is very important in clinical medicine to understand the course and estimate the progression of this demyelination disease. The lesions could be identified by the experts with brain magnetic resonance imaging (MRI) technology, especially the fluid attenuated inversion recovery sequence (FLAIR), which generates two-dimensional slices sampled from the three-dimensional space with specified slice thickness and increment values. Not every MRI scan, however, could be contiguous nor overlapping due to many reasons, to prevent from a drastic increase in the overall duration of the scans. Particularly, it is very hard to stabilize a child for hours in the same position; therefore, the specialists keep the scan procedure as short as possible, by increasing the slice thickness and more importantly, reducing the number of slices which cause some consistent gaps emerging between the slices and leading to inconclusive results. Given these facts, we propose a novel procedure to overcome this inadequacy by filling the gaps of incremental MRIs based on a Nakagami imaging and a content-based morphing method generating imaginary frames between the genuine MRI slices. Afterwards, the segmented images are reconstructed in three-dimensional space to estimate the lesion volumes for three consecutive scans of one patient. The results are greatly encouraging that we calculated 95.72% as the mean average percentage accuracy (MAPA) with 92.17% dice score (DSC%); while a little sacrifice in DSC% down to 90.35% provided us a better MAPA of 96.44%; while without morphing, the MAPA was calculated using only the binary ground truth (GT) images as 85.97%. As an expert system, the automated framework we presented would be very beneficial for volume estimations in clinics as well as visualizing the lesions and tracking the progression of MS disease.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30224 - Radiology, nuclear medicine and medical imaging

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Expert Systems with Applications

ISSN

0957-4174

e-ISSN

1873-6793

Volume of the periodical

235

Issue of the periodical within the volume

JAN

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

121250

UT code for WoS article

001067913600001

EID of the result in the Scopus database

2-s2.0-85168795556