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Head And Neck Tumor Histopathological Image Representation With Pre- Trained Convolutional Neural Network And Vision Transformer, Ranny Rahaningrum Herdiantoputri, Daisuke Komura, Tohru Ikeda, Shumpei Ishikawa

Journal of Dentistry Indonesia

Image representation via machine learning is an approach to quantitatively represent histopathological images of head and neck tumors for future applications of artificial intelligence-assisted pathological diagnosis systems. Objective: This study compares image representations produced by a pre-trained convolutional neural network (VGG16) to those produced by a vision transformer (ViT-L/14) in terms of the classification performance of head and neck tumors. Methods: W hole-slide images of five oral t umor categories (n = 319 cases) were analyzed. Image patches were created from manually annotated regions at 4096, 2048, and 1024 pixels and rescaled to 256 pixels. Image representations were …

N Y State Dent J August-September 2022

The New York State Dental Journal

In the August-September 2022 issue, the reader will find the following feature articles:

• Maxillary Sinus Foreign Body From an Unusual Source: Provisional Prosthesis Material
• Antihypertensive Drug-induced Orofacial Angioedema: Case Reports
• An Overview of Maxillofacial Rehabilitation for the General Dentist

This issue includes regular columns with regional news impacting the New York membership including: editorial and perspectives columns, legal, association activities, component news, continuing education opportunities, and classifieds.