A chance-constrained programming approach to preoperative planning of robotic cardiac surgery under task-level uncertainty

Hamidreza Azimian, Michael D. Naish, Bob Kiaii, Rajni V. Patel

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this paper, a novel formulation for robust surgical planning of robotics-assisted minimally invasive cardiac surgery based on patient-specific preoperative images is proposed. In this context, robustness is quantified in terms of the likelihood of intraoperative collisions and of joint limit violations. The proposed approach provides a more accurate and complete formulation than existing deterministic approaches in addressing uncertainty at the task level. Moreover, it is demonstrated that the dexterity of robotic arms can be quantified as a cross-entropy term. The resulting planning problem is rendered as a chance-constrained entropy maximization problem seeking a plan with the least susceptibility toward uncertainty at the task level, while maximizing the dexterity (cross-entropy term). By such treatment of uncertainty at the task level, spatial uncertainty pertaining to mismatches between the patient-specific anatomical model and that of the actual intraoperative situation is also indirectly addressed. As a solution method, the unscented transform is adopted to efficiently transform the resulting chance-constrained entropy maximization problem into a constrained nonlinear program without resorting to computationally expensive particle-based methods.

Original languageEnglish (US)
Article number6783687
Pages (from-to)612-622
Number of pages11
JournalIEEE Journal of Biomedical and Health Informatics
Volume19
Issue number2
DOIs
StatePublished - Mar 1 2015
Externally publishedYes

Keywords

  • Medical robotics
  • planning under uncertainty
  • port placement
  • stochastic programming
  • surgical planning

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

Fingerprint Dive into the research topics of 'A chance-constrained programming approach to preoperative planning of robotic cardiac surgery under task-level uncertainty'. Together they form a unique fingerprint.

Cite this