Intraoperative estimation of liver boundary conditions from multiple partial surfaces.

ABSTRACT:

Purpose

A computer-assisted surgical system must provide up-to-date and accurate information of the patient's anatomy during the procedure to improve clinical outcome. It is therefore essential to consider the tissue deformations, and a patient-specific biomechanical model (PBM) is usually adopted. The predictive capability of the PBM is highly influenced by proper definition of attachments to the surrounding anatomy, which are difficult to estimate preoperatively.

Methods

We propose to predict the location of attachments using a deep neural network fed with multiple partial views of the intraoperative deformed organ surface directly encoded as point clouds. Compared to previous works, providing a sequence of deformed views as input allows the network to consider the tempora

SUBMITTER: Mendizabal A 

PROVIDER: S-EPMC10329628 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature