3D segmentation of the head for assessing bone changes applied to Odontology.

• Grant number: 12/24036-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: July 01, 2013
• End date: November 30, 2017
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: João Do Espirito Santo Batista Neto
• Grantee: Oscar Alonso Cuadros Linares
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated scholarship(s): 15/12771-7 - 3D segmentation of the head for assessing bone changes in odontology, BE.EP.DR

Abstract

Computed tomography plays a key role in the diagnosis and treatment analysis, for example, changes in skull over time for applications in dentistry. This process is conducted by dentists, and consists of the use of tools that manipulate 3D data and generate segmentations of important anatomical structures. However, these tools are not satisfactory, since many targets produce false positives or false negatives. Moreover, it is often necessary to combine the functionality of not just one, but multiple tools to achieve a minimally satisfactory result, which is not a simple task for such professionals. The aim of this PhD project is to define, develop and refine techniques for interactive segmentation of 3D CT scans of the skull to identify important anatomic structures, allowing experts to extract for therapeutic measures. Once the scans to be used in this project have high resolution, segmentation will be performed in three steps: 1) pre-segmentation to reduce the resolution of CT, 2) segmentation of structures main image and 3) interactivity with the user to refine the segmentation. The pre-segmentation techniques will be performed by grouping voxels with similar properties, called Super voxels. Segmentation of structures will be made by means of algorithms for detecting communities in complex networks, and the interactivity with the user is based on pre-segmentation of similar voxels, so as to take advantage of their knowledge to refine the segmentation. It is hoped that this project contributes to the state of the art of 3D segmentation of CT scans of the skull, enhance and develop methods capable of segmenting high-resolution volumes in acceptable computational times.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LINARES, OSCAR CUADROS; BIANCHI, JONAS; RAVELI, DIRCEU; BATISTA NETO, JOAO; HAMANN, BERND. Mandible and skull segmentation in cone beam computed tomography using super-voxels and graph clustering. VISUAL COMPUTER, v. 35, n. 10, p. 1461-1474, OCT 2019. (12/24036-1, 15/12771-7)

LINARES, OSCAR CUADROS; HAMANN, BERND; BATISTA NETO, JOAO. Segmenting Cellular Retinal Images by Optimizing Super-Pixels, Multi-Level Modularity, and Cell Boundary Representation. IEEE Transactions on Image Processing, v. 29, p. 809-818, 2020. (18/06074-0, 12/24036-1)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

LINARES, Oscar Alonso Cuadros. Mandible and Skull Segmentation in Cone Bean Computed Tomography Data. 2017. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.