Publications

Authors:

Visani, Valentina; Natale, Valerio; Colombi, Annalisa; Tamanti, Agnese; Bertoldo, Alessandra; Marjin, Corina; Ricciardi, GIUSEPPE KENNETH; Pizzini, Francesca Benedetta; Calabrese, Massimiliano; Castellaro, Marco

Title:

Impact of model selection procedure on Deep Neural Networks ensemble for the Choroid Plexus segmentation in Multiple Sclerosis

Year:

2023

Type of item:

Contributo in atti di convegno

Tipologia ANVUR:

Contributo in Atti di convegno

Language:

Inglese

Format:

Elettronico

Congresso:

8th National Congress of Bioengineering, GNB 2023

Place:

Padova

Period:

21-23 June 2023

Publisher:

Patron

Page numbers:

1-4

Keyword:

Choroid Plexus; Deep Neural Networks; Multiple Sclerosis; Semantic Segmentation

Short description of contents:

The Choroid Plexus (ChP) is a brain vascular tissue involved in regulatory processes. ChP Volume (ChPV) modifications are related to neurodegenerative disorders. Therefore, ChPV, that can be obtained from manual segmentation of brain MRI, is an imaging biomarker candidate to monitor disease evolution. This work proposes a method for the automatic segmentation of ChP based on hyperparameters optimization of Deep Neural Networks (DNNs). Twenty-Seven hyperparameters and architectures combinations were trained on T1-w MRI with two different selection strategies: select the best models using the routinely used Dice Coefficient and combining it to the Absolute Percentage Volume Difference. The selection of the ten best models was made on bias and variance of Absolute Percentage Volume Difference and best DNNs were ensembled by majority voting for both selection strategies. The proposed ensemble models outperform single DNNs (Dice Coefficient for both ensembles: 0.81±0.07; Percentage Volume Difference - ensemble Dice: 0.41±10.75%; ensemble Dice&Volume: -0.05±10.49%). Ensemble segmentations obtained using the combination of Dice and Absolute Percentage Volume Difference are preferable since the variance obtained in the testing phase is slightly lower than the commonly used Dice metric. Therefore, the proposed ensemble of DNNs, selected exploiting both Dice and Absolute Percentage Volume Difference, is a promising tool to obtain automatic quantification of the ChPV. © 2023 Convegno Nazionale di Bioingegneria. All rights reserved.

Web page:

https://www.grupponazionalebioingegneria.it/it/publication/eighth-national-congress-of-bioengineering-proceedings-2023/

Product ID:

143076

Handle IRIS:

11562/1146811

Last Modified:

December 11, 2024

Bibliographic citation:

Visani, Valentina; Natale, Valerio; Colombi, Annalisa; Tamanti, Agnese; Bertoldo, Alessandra; Marjin, Corina; Ricciardi, GIUSEPPE KENNETH; Pizzini, Francesca Benedetta; Calabrese, Massimiliano; Castellaro, Marco, Impact of model selection procedure on Deep Neural Networks ensemble for the Choroid Plexus segmentation in Multiple Sclerosis  in 8th National Congress of Bioengineering, GNB 2023. Proceedings , Patron , Proceedings of "8th National Congress of Bioengineering, GNB 2023" , Padova , 21-23 June 2023 , 2023 , pp. 1-4

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