Efficient Semiautomatic Segmentation of Plant Biological Objects Based on Live-wire Methods

Abstract

This paper presents a novel method for efficient semiautomatic multi-label segmentation of plant biological image data. The approach extends live-wire methods in order to facilitate exact user-steered segmentations for atlas generation. By integrating a segmentation-specific user interaction model into the live-wire formulation i) more exact segmentations, ii) increased computational efficiency, iii) without loss of generality are achieved. The concept of mutual influence of image feature based path costs and user input uncertainty are consistently combined. By incorporating user behavior into cost based delineation a more intuitive user interface is obtained also yielding in a more accurate segmentation. We introduce path-based methodologies, specific user interaction models and propose the combination of both of them. The purposefulness of the method is shown in an application comprising segmentation of histological section data supporting the generation of 3-D atlases.