Multiregional Soft Segmentation Driven by Modified ABC Algorithm and Completed by Spatial Aggregation: Volumetric, Spatial Modelling and Features Extraction of Articular Cartilage Early Loss

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241593" target="_blank" >RIV/61989100:27240/18:10241593 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-75420-8_37" target="_blank" >http://dx.doi.org/10.1007/978-3-319-75420-8_37</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-75420-8_37" target="_blank" >10.1007/978-3-319-75420-8_37</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multiregional Soft Segmentation Driven by Modified ABC Algorithm and Completed by Spatial Aggregation: Volumetric, Spatial Modelling and Features Extraction of Articular Cartilage Early Loss

Popis výsledku v původním jazyce

In a clinical practise of the orthopaedics and medical imaging systems, the early cartilage loss, and cartilage lesions are challenging tasks. Due to an insufficient contrast, such pathologies are badly observable by naked eyes. Furthermore, objectification and quantification of those pathological findings are usually only subjectively estimated without the SW support. We propose a multiregional segmentation model based on the histogram classification with using of a sequence of triangular fuzzy functions where each such function represents specific knee area. To ensure a robustness of the model, respective fuzzy class location is driven by the ABC (Artificial Bee Colony) genetic algorithm respecting statistical features of the physiological cartilage. In the second step of the algorithm, a spatial aggregation is applied in order to consider spatial relationships in every region to prevent the image noise deterioration. Such multiregional segmentation model allows for an extraction of significant features well corresponding with the early cartilage loss like is the cartilage volume.

Název v anglickém jazyce

Multiregional Soft Segmentation Driven by Modified ABC Algorithm and Completed by Spatial Aggregation: Volumetric, Spatial Modelling and Features Extraction of Articular Cartilage Early Loss

Popis výsledku anglicky

In a clinical practise of the orthopaedics and medical imaging systems, the early cartilage loss, and cartilage lesions are challenging tasks. Due to an insufficient contrast, such pathologies are badly observable by naked eyes. Furthermore, objectification and quantification of those pathological findings are usually only subjectively estimated without the SW support. We propose a multiregional segmentation model based on the histogram classification with using of a sequence of triangular fuzzy functions where each such function represents specific knee area. To ensure a robustness of the model, respective fuzzy class location is driven by the ABC (Artificial Bee Colony) genetic algorithm respecting statistical features of the physiological cartilage. In the second step of the algorithm, a spatial aggregation is applied in order to consider spatial relationships in every region to prevent the image noise deterioration. Such multiregional segmentation model allows for an extraction of significant features well corresponding with the early cartilage loss like is the cartilage volume.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-03037S" target="_blank" >GA17-03037S: Hodnocení investic do vývoje zdravotních prostředků</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 10752

ISBN

978-3-319-75419-2

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

10

Strana od-do

385-394

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Dong Hoi

Datum konání akce

19. 3. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000453510500037