Spatio temporal analysis of pediatric magnetic resonance images

• Grant number: 17/50236-1
• Support Opportunities: Regular Research Grants
• Start date: July 01, 2018
• End date: June 30, 2022
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Agreement: ANR
• Principal Investigator: Roberto Marcondes Cesar Junior
• Grantee: Roberto Marcondes Cesar Junior
• Principal researcher abroad: Isabelle Bloch
• Institution abroad: ParisTech, France
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The advances in medical image analysis still leave a gap regarding pediatric brain imaging, even though \here is an regarding medical demand. This project aims at contributing to fill this gap, focusing on brain magnetic resonance Imaging (MRI) of infants, newborns and premature babies, which raise specific issues due to the particular grey/white matter contrast related to the physiological myelination process, How to extract and understand meaningful patters from data is a fundamental question scenarios where data are scarce but expert knowledge, continuously enriched, is available. This is typically the case here. We propose to develop structural representations of Knowledge and image information in the form of graphs and hypergraphs, which will be exploited to guide spatio-temporal segmentation, recognition and quantification processes. The aim is to aid diagnosis, pathology analysis and patients' folia -up. Applications will include the analysis of hyperintensities on the white matter, the volumetry of corpus callosum and its evolution, and neuro-oncology with the study of the influence of tumors on surrounding structures over time. The project involves specialists in medical image analysis, structural knowledge representation and pediatric radiology. (AU)

Scientific publications

(5)

(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)

OLIVEIRA, HUGO; PENTEADO, LARISSA; MACIEL, JOSE LUIZ; FERRACIOLLI, SUELY FAZIO; TAKAHASHI, MARCELO STRAUS; BLOCH, ISABELLE; CESAR JUNIOR, ROBERTO; IEEE COMP SOC. Automatic Segmentation of Posterior Fossa Structures in Pediatric Brain MRIs. 2021 34TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI 2021), v. N/A, p. 8-pg., 2021-01-01. (19/16112-9, 15/22308-2, 18/07386-5, 20/06744-5, 17/50236-1)

GAMA, PEDRO HENRIQUE TARGINO; OLIVEIRA, HUGO; DOS SANTOS, JEFERSSON A.; CESAR JR, ROBERTO M.. An overview on Meta-learning approaches for Few-shot Weakly-supervised Segmentation. COMPUTERS & GRAPHICS-UK, v. 113, p. 12-pg., 2023-05-28. (15/22308-2, 17/50236-1, 20/06744-5)

RIVA, MATEUS; GORI, PIETRO; YGER, FLORIAN; BLOCH, ISABELLE; IEEE. IS THE U-NET DIRECTIONAL-RELATIONSHIP AWARE?. 2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, v. N/A, p. 5-pg., 2022-01-01. (17/50236-1, 15/22308-2)

NUNES, IAN; LARANJEIRA, CAMILA; OLIVEIRA, HUGO; DOS SANTOS, JEFERSSON A.. A systematic review on open-set segmentation. COMPUTERS & GRAPHICS-UK, v. 115, p. 13-pg., 2023-10-01. (15/22308-2, 17/50236-1, 20/06744-5)

CHAMORRO MARTINEZ, JORGE A.; OLIVEIRA, HUGO; DOS SANTOS, JEFERSSON A.; FEITOSA, RAUL QUEIROZ. Open Set Semantic Segmentation for Multitemporal Crop Recognition. IEEE Geoscience and Remote Sensing Letters, v. 19, 2022. (17/50236-1, 20/06744-5, 15/22308-2)