Content-based retrieval of medical images to aid the clinical decision using radiomics

• Grant number: 17/23780-2
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: August 01, 2018
• End date: March 31, 2021
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computational Mathematics
• Principal Investigator: Agma Juci Machado Traina
• Grantee: Jonathan da Silva Ramos
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD), AP.TEM

Abstract

Nowadays there is a huge amount of images daily produced. There is no difference in the medical scenario, in which a lot of images are produced in many exams and need to be stored and analyzed. However, the manual analysis and annotation is a time consuming task and requires a great knowledge for each image analyzed. To aid in this task, content-based image retrieval - CBIR systems are widely used. Notwithstanding, CBIR systems are mostly isolated systems that seeks just one output (anomaly or no anomaly present). To improve even more CBIR systems, the radiomics systems were proposed, which aims at extracting as many features as possible from the images and combine them with other clinical data. In the end, those information can be mined and analyzed, improving the individual treatment and patient tracking. On the other hand, there are many challenges to implement a radiomics system. This doctoral project aims at advancing in the CBIR and CAD fields by integrating the radiomics system, seeking to maximize to the highest level the security and confidence of those systems. Initially, we are working with spinal images, which presents a considerable challenge when there is deformation or lesions present. The project's contributions will be analyzed by specialists in the Hospital das Clínicas in the medicine faculty in Ribeirão Preto - HCFMRP, within the thematic FAPESP project MIVisBD. (AU)

Scientific publications

(6)

(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)

RAMOS, JONATHAN S.; CAZZOLATO, MIRELA T.; NOGUEIRA-BARBOSA, MARCELLO H.; TRAINA, AGMA J. M.; ACM. FINE: Improving time and precision of segmentation techniques for vertebral compression fractures in MRI. PROCEEDINGS OF THE 35TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING (SAC'20), v. N/A, p. 4-pg., 2020-01-01. (18/24414-2, 16/17078-0, 17/23780-2)

RAMOS, JONATHAN S.; CAZZOLATO, MIRELA T.; FAICAL, BRUNO S.; NOGUEIRA-BARBOSA, MARCELLO H.; TRAINA, CAETANO, JR.; TRAINA, AGMA J. M.; IEEE. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging. 2019 IEEE 32ND INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), v. N/A, p. 6-pg., 2019-01-01. (18/24414-2, 17/23780-2, 18/06228-7, 16/17078-0)

CAZZOLATO, MIRELA T.; RAMOS, JONATHAN S.; RODRIGUES, LUCAS S.; SCABORA, LUCAS C.; CHINO, DANIEL Y. T.; JORGE, ANA E. S.; DE AZEVEDO-MARQUES, PAULO MAZZONCINI; TRAINA JR, CAETANO; TRAINA, AGMA J. M.; DEHERRERA, AGS; et al. Semi-Automatic Ulcer Segmentation and Wound Area Measurement Supporting Telemedicine. 2020 IEEE 33RD INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS(CBMS 2020), v. N/A, p. 6-pg., 2020-01-01. (16/17078-0, 20/07200-9, 17/23780-2, 18/24414-2, 16/17330-1)

RAMOS, JONATHAN S.; MACIEL, JAMILLY G.; CAZZOLATO, MIRELA T.; TRAINA JR, CAETANO; NOGUEIRA-BARBOSA, MARCELLO H.; TRAINA, AGMA J. M.; ALMEIDA, JR; GONZALEZ, AR; SHEN, L; KANE, B; et al. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging. 2021 IEEE 34TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), v. N/A, p. 6-pg., 2021-01-01. (20/11258-2, 17/23780-2, 20/07200-9, 16/17078-0, 18/04266-9)

RAMOS, JONATHAN S.; CAZZOLATO, MIRELA T.; FAICAL, BRUNO S.; LINARES, OSCAR A. C.; NOGUEIRA-BARBOSA, MARCELLO H.; TRAINA, CAETANO, JR.; TRAINA, AGMA J. M.; IEEE. Fast and smart segmentation of paraspinal muscles in magnetic resonance imaging with CleverSeg. 2019 32ND SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), v. N/A, p. 8-pg., 2019-01-01. (18/24414-2, 16/17078-0, 17/23780-2, 18/06228-7)

RAMOS, JONATHAN S.; WATANABE, CAROLINA Y. V.; NOGUEIRA-BARBOSA, MARCELLO H.; TRAINA, AGMA J. M.; ASSOC COMP MACHINERY. BGrowth: an efficient approach for the segmentation of vertebral compression fractures in magnetic resonance imaging. SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING, v. N/A, p. 8-pg., 2019-01-01. (17/23780-2, 16/17078-0)

Academic Publications

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

RAMOS, Jonathan da Silva. Analysis of medical images to support decision-making in the musculoskeletal field. 2021. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.