Tau protein discrete aggregates in Alzheimer's disease: Neuritic plaques and tangles detection and segmentation using computational histopathology

K. Manoušková, V. Abadie, M. Ounissi, G. Jimenez, L. Stimmer, B. Delatour, S. Durrleman, Daniel Racoceanu

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

Tau proteins in the gray matter are widely known to be a part of Alzheimer's disease symptoms. They can aggregate in three different structures within the brain: neurites, tangles, and neuritic plaques. The morphology and the spatial disposition of these three aggregates are hypothesised to be correlated to the advancement of the disease. In order to establish a behavioural disease model related to the Tau proteins aggregates, it is necessary to develop algorithms to detect and segment them automatically. We present a 5-folded pipeline aiming to perform with clinically operational results. This pipeline is composed of a non-linear colour normalisation, a CNN-based image classifier, an Unet-based image segmentation stage, and a morphological analysis of the segmented objects. The tangle detection and segmentation algorithms improve state-of-the-art performances (75.8% and 91.1% F1- score, respectively), and create a reference for neuritic plaques detection and segmentation (81.3% and 78.2% F1-score, respectively). These results constitute an initial baseline in an area where no prior results exist, as far as we know. The pipeline is complete and based on a promising state-of-the-art architecture. Therefore, we consider this study a handy baseline of an impactful extension to support new advances in Alzheimer's disease. Moreover, building a fully operational pipeline will be crucial to create a 3D histology map for a deeper understanding of clinico-pathological associations in Alzheimer's disease and the histology-based evidence of disease stratification among different sub-types.

Idioma originalInglés
Título de la publicación alojadaMedical Imaging 2022
Subtítulo de la publicación alojadaDigital and Computational Pathology
EditoresJohn E. Tomaszewski, Aaron D. Ward, Richard M. Levenson
EditorialSPIE
ISBN (versión digital)9781510649538
DOI
EstadoPublicada - 2022
Publicado de forma externa
EventoMedical Imaging 2022: Digital and Computational Pathology - Virtual, Online
Duración: 21 mar. 202227 mar. 2022

Serie de la publicación

NombreProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volumen12039
ISSN (versión impresa)1605-7422

Conferencia

ConferenciaMedical Imaging 2022: Digital and Computational Pathology
CiudadVirtual, Online
Período21/03/2227/03/22

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