A Dataset of Anatomical Environments for Medical Robots: Modeling Respiratory Deformation

TL;DR

This paper introduces a publicly available dataset of lung anatomical environments with modeled respiratory deformation, aiding medical robot design, benchmarking, and simulation by providing standardized, patient-derived models.

Contribution

It provides a novel collection of lung environments with respiratory deformation models, addressing the lack of shared, standardized anatomical datasets for medical robotics.

Findings

Shared environments facilitate benchmarking and comparison.

Modeling respiratory deformation improves simulation accuracy.

Public dataset enhances reproducibility and collaboration.

Abstract

Anatomical models of a medical robot's environment can significantly help guide design and development of a new robotic system. These models can be used for benchmarking motion planning algorithms, evaluating controllers, optimizing mechanical design choices, simulating procedures, and even as resources for data generation. Currently, the time-consuming task of generating these environments is repeatedly performed by individual research groups and rarely shared broadly. This not only leads to redundant efforts, but also makes it challenging to compare systems and algorithms accurately. In this work, we present a collection of clinically-relevant anatomical environments for medical robots operating in the lungs. Since anatomical deformation is a fundamental challenge for medical robots operating in the lungs, we describe a way to model respiratory deformation in these environments using patient-derived data. We share the environments and deformation data publicly by adding them to the Medical Robotics Anatomical Dataset (Med-RAD), our public dataset of anatomical environments for medical robots.