Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

Journal: Neurosurgical focus
Published Date: Jun 1, 2023

Abstract

OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the cavernous carotid region. The authors evaluated a deep learning pipeline for segmentation of vessels and IAs from CTA using coregistered, segmented DSA images as ground truth.

Authors

  • Tatsat R Patel
    1Canon Stroke and Vascular Research Center.
  • Aakash Patel
    Dunedin School of Medicine, Dunedin Hospital, Dunedin, New Zealand.
  • Sricharan S Veeturi
    1Canon Stroke and Vascular Research Center.
  • Munjal Shah
    1Canon Stroke and Vascular Research Center.
  • Muhammad Waqas
    Department of Botanical and Environmental Science, Kohat University of Science and Technology, Kohat, 26000, Khyber Pakhtunkhwa, Pakistan.
  • Andre Monteiro
    1Canon Stroke and Vascular Research Center.
  • Ammad A Baig
    1Canon Stroke and Vascular Research Center.
  • Nandor Pinter
    1Canon Stroke and Vascular Research Center.
  • Elad I Levy
    Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA; Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York, USA; Department of Neurosurgery, University at Buffalo, Buffalo, New York, USA.
  • Adnan H Siddiqui
    2Canon Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, New York.
  • Vincent M Tutino
    2Canon Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, New York.

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