NeuroImage: Clinical (Jan 2020)

pBrain: A novel pipeline for Parkinson related brain structure segmentation

  • José V. Manjón,
  • Alexa Bertó,
  • José E. Romero,
  • Enrique Lanuza,
  • Roberto Vivo-Hernando,
  • Fernando Aparici-Robles,
  • Pierrick Coupe

Journal volume & issue
Vol. 25

Abstract

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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.