| Literature DB >> 24332441 |
Daniel Barbosa1, Brecht Heyde2, Maja Cikes2, Thomas Dietenbeck3, Piet Claus2, Denis Friboulet3, Olivier Bernard3, Jan D'hooge2.
Abstract
Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.Keywords: Active contours; B-spline explicit active surfaces; Interactive segmentation; User interaction
Mesh:
Year: 2013 PMID: 24332441 DOI: 10.1016/j.compmedimag.2013.10.002
Source DB: PubMed Journal: Comput Med Imaging Graph ISSN: 0895-6111 Impact factor: 4.790