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2024 | OriginalPaper | Buchkapitel

Implementation of Vision Transformers on SPECT Heart Dataset: A Comparative Study

verfasst von : Poonam Verma, Vikas Tripathi, Bhaskar Pant

Erschienen in: Advances in Data-Driven Computing and Intelligent Systems

Verlag: Springer Nature Singapore

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Abstract

Medical imaging has gone through many changes and one of the changes could be observed since the introduction of transformers and deep learning models. Transformers have complicated architecture that can help in carrying out complex tasks on medical images or data. This research paper presents a comprehensive study on the implementation of the Vision Transformers (ViTs) on the Single-Photon Emission Computed Tomography (SPECT) heart dataset. The basic objective is to evaluate the accuracy of the classification of abnormal cardiac conditions from SPECT images using ViT. Further, this paper tries to explore different aspects of the architecture of transformers and their performance in comparison to the traditional machine learning models in analyzing the SPECT heart dataset. It helps to contribute to the growing community of research carried out in medical images and data using new technologies.

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Titel: Implementation of Vision Transformers on SPECT Heart Dataset: A Comparative Study
verfasst von: Poonam Verma
Vikas Tripathi
Bhaskar Pant
Verlag: Springer Nature Singapore
Buch: Advances in Data-Driven Computing and Intelligent Systems
Print ISBN: 978-981-9995-20-2

Electronic ISBN: 978-981-9995-21-9

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-99-9521-9_10

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