Geodesic
Sternum Age Estimation with Dual Channel Fusion CNN Model
Computer Science and Information Systems, Tome 20 (2023) no. 1.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

Although age determination by radiographs of the hand and wrist before the age of 18 is an area where there is a lot of radiological knowledge and many studies are carried out, studies on age determination for adults are limited. Studies on adult age determination through sternum multidetector computed tomography (MDCT) images using artificial intelligence algorithms are much fewer. The reason for the very few studies on adult age determination is that most of the changes observed in the human skeleton with age are outside the limits of what can be perceived by the human eye. In this context, with the dual-channel Convolutional Neural Network (CNN) we developed, we were able to predict the age groups defined as 20-35, 35-50, 51-65, and over 65 with 73% accuracy over sternum MDCT images. Our study shows that fusion modeling with dual-channel convolutional neural networks and using more than one image from the same patient is more successful. Fusion models will make adult age determination, which is often a problem in forensic medicine, more accurate.
Keywords: Sternum age; deep fusion CNN, CNN age estimation, dual channel fusion CNN, sternum with CNN 
@article{CSIS_2023_20_1_a14,
     author = {Fuat T\"URK and Mustafa KAYA and Burak Mert AKHAN and S\"umeyra \c{C}AYIR\"OZ and Erhan ILGIT},
     title = {Sternum {Age} {Estimation} with {Dual} {Channel} {Fusion} {CNN} {Model}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {20},
     number = {1},
     year = {2023},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a14/}
}
TY  - JOUR
AU  - Fuat TÜRK
AU  - Mustafa KAYA
AU  - Burak Mert AKHAN
AU  - Sümeyra ÇAYIRÖZ
AU  - Erhan ILGIT
TI  - Sternum Age Estimation with Dual Channel Fusion CNN Model
JO  - Computer Science and Information Systems
PY  - 2023
VL  - 20
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a14/
ID  - CSIS_2023_20_1_a14
ER  - 
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%A Mustafa KAYA
%A Burak Mert AKHAN
%A Sümeyra ÇAYIRÖZ
%A Erhan ILGIT
%T Sternum Age Estimation with Dual Channel Fusion CNN Model
%J Computer Science and Information Systems
%D 2023
%V 20
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a14/
%F CSIS_2023_20_1_a14
Fuat TÜRK; Mustafa KAYA; Burak Mert AKHAN; Sümeyra ÇAYIRÖZ; Erhan ILGIT. Sternum Age Estimation with Dual Channel Fusion CNN Model. Computer Science and Information Systems, Tome 20 (2023) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2023_20_1_a14/