A Supervoxel-Based Solution to Resume Segmentation for Interactive Correction by Differential Image-Foresting Transforms

Author(s)

Moreira Tavares, Anderson Carlos ; Vechiatto Miranda, Paulo Andre ; Spina, Thiago Vallin ; Falcao, Alexandre Xavier ; Angulo, J ; VelascoForero, S ; Meyer, F

• Document type: Journal article
• Source: MATHEMATICAL MORPHOLOGY AND ITS APPLICATIONS TO SIGNAL AND IMAGE PROCESSING (ISMM 2017); v. 10225, p. 12-pg., 2017-01-01.

Abstract

The foolproof segmentation of 3D anatomical structures in medical images is usually a challenging task, which makes automatic results often far from desirable and interactive repairs necessary. In the past, we introduced a first solution to resume segmentation from third-party software into an initial optimum-path forest for interactive correction by differential image foresting transforms (DIFTs). Here, we present a new method that estimates the initial forest (input segmentation) rooted at more regularly separated seed voxels to facilitate interactive editing. The forest is a supervoxel segmentation from seeds that result from a sequence of image foresting transforms to conform as much as possible the supervoxel boundaries to the boundaries of the object in the input segmentation. We demonstrate the advantages of the new method over the previous one by using a robot user, as an impartial way to correct brain segmentation in MR-T1 images. (AU)

• FAPESP's process: 16/11853-2 - SAMSAM: Segmentation for Analysis and Measurements in the Shoot Apical Meristem
• Grantee: Thiago Vallin Spina
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• FAPESP's process: 15/09446-7 - Medical Image Segmentation: How to integrate object appearance/shape models and interactive correction with minimum user intervention?
• Grantee: Thiago Vallin Spina
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
• Grantee: Roberto Marcondes Cesar Junior
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
• Grantee: Alexandre Xavier Falcão
• Support Opportunities: Research Projects - Thematic Grants