Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images
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Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT ImagesAutor(es)
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2023Cita bibliográfica
P. L. Vidal, J. de Moura, J. Novo, M. Ortega and J. S. Cardoso, "Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10095039.
Resumo
[Abstract]: Optical Coherence Tomography (OCT) is the major diagnostic tool for the leading cause of blindness in developed countries: Diabetic Macular Edema (DME). Depending on the type of fluid accumulations, different treatments are needed. In particular, Cystoid Macular Edemas (CMEs) represent the most severe scenario, while Diffuse Retinal Thickening (DRT) is an early indicator of the disease but a challenging scenario to detect. While methodologies exist, their explanatory power is limited to the input sample itself. However, due to the complexity of these accumulations, this may not be enough for a clinician to assess the validity of the classification. Thus, in this work, we propose a novel approach based on multi-prototype networks with vision transformers to obtain an example-based explainable classification. Our proposal achieved robust results in two representative OCT devices, with a mean accuracy of 0.9099 ± 0.0083 and 0.8582 ± 0.0126 for CME and DRT-type fluid accumulations, respectively.
Palabras chave
Multi-Prototype
Transformers
Optical Coherence Tomography
Diabetic Macular Edema
Explainable Artificial Intelligence
Transformers
Optical Coherence Tomography
Diabetic Macular Edema
Explainable Artificial Intelligence
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https://doi.org/10.1109/ICASSP49357.2023.10095039 Presentado en: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 04-10 June 2023
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