pBrain: A novel pipeline for Parkinson related brain structure segmentation

José V. Manjón (1) , Alexa Bertó , José E. Romero (1) , Enrique Lanuza (2) , Roberto Vivo-Hernando , Fernando Aparici-Robles , Pierrick Coupé (3, 4)

1 ITACA
2 UV - Universitat de València
3 LaBRI - Laboratoire Bordelais de Recherche en Informatique
4 PICTURA - Patch-based processing for medical and natural images

Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson`s disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus). The proposed method is based on the multi-atlas label fusion technology that works on standard and high-resolution T2-weighted images. The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The proposed method has been compared to other state-of-the-art methods showing competitive results in terms of accuracy and execution time.

Domaines: Imagerie médicale

José V. Manjón, Alexa Bertó, José E. Romero, Enrique Lanuza, Roberto Vivo-Hernando, et al.. pBrain: A novel pipeline for Parkinson related brain structure segmentation. Neuroimage-Clinical, 2020, 25, pp.102184. ⟨10.1016/j.nicl.2020.102184⟩. ⟨hal-02481502⟩