Titre :	Deep Learning for Medical Object Detection and Segmentation : Case of Osteoarthritis Disease
Type de document :	texte imprimé
Auteurs :	Ouassim boukhennoufa, Auteur ; Aymen kara mahammed, Auteur ; Abdelouahab Moussaoui, Directeur de thèse
Année de publication :	2022
Importance :	1 vol (105 f .)
Format :	29cm
Langues :	Français (fre)
Catégories :	Thèses & Mémoires:Informatique
Mots-clés :	Transfer learning Vision transformers
Index. décimale :	004 Informatique
Résumé :	Osteoarthritis disease is mainly caused due to the damage to the knee joints, and since it is damaged, and diagnosed at late stages, there is almost no chance to reverse and cure the bone, which means that the patient will lose the ability to walk in a normal way and doing physical activities, and may entirely lose the use of his knees. In this thesis we want to propose novel classification models based on deep learning that will be able to classify and identify different grades of the osteoarthritis disease, and also object detectors to compare them to the classification models. We propose seven customized transfer learning models, we also proposed 7 Vision transformers models. In order to evaluate our model, we have compared the diagnosis of 6 experts in relation to deep learning with the performance of our models. Our proposed models outperformed the diagnosis of the previously published works using the same data, where we obtained an accuracy of up to 93.87% with early-stage detection. In addition, object detection approaches were proposed based on YoLo to compare them to classification models.
Côte titre :	MAI/0617
En ligne :	https://drive.google.com/file/d/1wy5MIfktmP63KzGlInLn58_HPt-I2S7r/view?usp=share [...]
Format de la ressource électronique :	pdf

Deep Learning for Medical Object Detection and Segmentation : Case of Osteoarthritis Disease [texte imprimé] / Ouassim boukhennoufa, Auteur ; Aymen kara mahammed, Auteur ; Abdelouahab Moussaoui, Directeur de thèse . - 2022 . - 1 vol (105 f .) ; 29cm.
Langues : Français (fre)

Catégories :	Thèses & Mémoires:Informatique
Mots-clés :	Transfer learning Vision transformers
Index. décimale :	004 Informatique
Résumé :	Osteoarthritis disease is mainly caused due to the damage to the knee joints, and since it is damaged, and diagnosed at late stages, there is almost no chance to reverse and cure the bone, which means that the patient will lose the ability to walk in a normal way and doing physical activities, and may entirely lose the use of his knees. In this thesis we want to propose novel classification models based on deep learning that will be able to classify and identify different grades of the osteoarthritis disease, and also object detectors to compare them to the classification models. We propose seven customized transfer learning models, we also proposed 7 Vision transformers models. In order to evaluate our model, we have compared the diagnosis of 6 experts in relation to deep learning with the performance of our models. Our proposed models outperformed the diagnosis of the previously published works using the same data, where we obtained an accuracy of up to 93.87% with early-stage detection. In addition, object detection approaches were proposed based on YoLo to compare them to classification models.
Côte titre :	MAI/0617
En ligne :	https://drive.google.com/file/d/1wy5MIfktmP63KzGlInLn58_HPt-I2S7r/view?usp=share [...]
Format de la ressource électronique :	pdf