Brazil

THE PROJECT - Cell Recognition for Inspection of Cervix (CRIC)

This project aims to develop organized image catalogues and software dedicated to cell morphology and recognition, targeting cervical cells. Current database contains cervical cell images from Brazilian women that depend upon the public health system, known as SUS in Brazil. Our teams have built analytical and data-driven models using information from datasets provided by the Federal University of Ouro Preto and Federal University of Ceara. The cell database contains digital pictures from conventional Pap smears, which are part of the visual search paper we have just submitted and is under review with IEEE TIP. Updates coming soon.

Principal investigators:

• Profa. Dra. Andrea G. C. Bianchi, Computer Science Dept, UFOP
• Profa. Dra. Cláudia M. Carneiro, Pathology Dept , UFOP
• Profa. Dra. Fatima N. S. de Medeiros, Engineering Division - UFC
• Dra. Daniela M. Ushizima, Computer Science Division, Berkeley Lab e UC Berkeley

Co-investigators:

• Dra. Alessandra Gomes, Cytology/Pathology, UFOP
• Prof. MSc. Flávio Henrique Duarte de Araújo, CS, UFC-UFPI
• Prof. MSc. Paulo Calaes, CS, UFOP
• Prof. MSc. Romuere Rodrigues Veloso e Silva, CS, UFC-UFPI

Collaborating researchers:

• MSc. Alan Carneiro, UFOP
• Prof. MSc. Daniel Silva Ferreira, IFCE
• Prof. Dr. Geraldo Luis Bezerra Ramalho, IFCE
• Dr. Luis Augusto Consularo
• Prof. Dr. Marcelo Marques Simões de Souza, UFC
• MSc. Mariana Trevisan Rezende, UFOP
• Prof. Dr. Regis Cristiano Pinheiro Carvalho, IFCE
• Prof. Dra. Silvia Cristina Pinto, UERJ

Suporte:

• Brasil: CAPES, CNPq
• USA: BIDS (Moore and Sloan Foundation)

More: [History] [News] [1st place code] [American-Canadian-Australian codes]

More about CRIC 2015 and CRIC 2016: https://sites.google.com/site/cervicalcancercell/home

Previous meetings:

Join us at the CRIC Conference 2017 in Fortaleza, Ceara from June 26th to June 28 & Hackathon July 3rd-4th at UFC DETI Auditory, Bloco 725, check our new algorithms and software, and be part of this amazing initiative to improve human health.

Learn with our team about image analysis, pathology, materials design, computer vision and machine learning.