Triplet-Loss Based Siamese Convolutional Neural Network for 4-Way Classification of Alzheimer’s Disease

Noushath Shaffi*, Faizal Hajamohideen, Mufti Mahmud, Abdelhamid Abdesselam, Karthikeyan Subramanian, Arwa Al Sariri

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

8 اقتباسات (Scopus)

ملخص

Alzheimer’s disease (AD) is a neurodegenerative disease that causes irreversible damage to several brain regions including the hippocampus causing impairment in cognition, function and behaviour. Earlier diagnosis of the disease will reduce the suffering of the patients and their family members. Towards that aim, this paper presents a Siamese Convolutional Neural Network (CNN) based model using the Triplet-loss function for the 4-way classification of AD. We evaluated our models using both pre-trained and non-pre-trained CNNs. The models’ efficacy was tested on the OASIS dataset and obtained satisfactory results under a data-scarce real-time environment.

اللغة الأصليةEnglish
عنوان منشور المضيفLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
المحررونMufti Mahmud, Jing He, Stefano Vassanelli, André van Zundert, Ning Zhong
ناشرSpringer Science and Business Media Deutschland GmbH
الصفحات277-287
عدد الصفحات11
رقم المعيار الدولي للكتب (المطبوع)9783031150364
المعرِّفات الرقمية للأشياء
حالة النشرPublished - يناير 1 2022
الحدث15th International Conference on Brain Informatics, BI 2022 - Virtual, Online
المدة: يوليو ١٥ ٢٠٢٢يوليو ١٧ ٢٠٢٢

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت13406 LNAI
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349

Conference

Conference15th International Conference on Brain Informatics, BI 2022
المدينةVirtual, Online
المدة٧/١٥/٢٢٧/١٧/٢٢

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