FINE: Improving time and precision of segmentation techniques for vertebral compression fractures in MRI

Autor(es)

Ramos, Jonathan S. ; Cazzolato, Mirela T. ; Nogueira-Barbosa, Marcello H. ; Traina, Agma J. M. ; ACM

• Tipo de documento: Artigo Científico
• Fonte: PROCEEDINGS OF THE 35TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING (SAC'20); v. N/A, p. 4-pg., 2020-01-01.

Resumo

Lower back pain is often related to spinal diseases. In particular, Vertebral Compression Fractures (VCFs) can impair mobility and compromise quality of life. In a Computer-Aided Diagnosis (CAD) context, the segmentation of VCFs is a challenging task due to non-homogeneous intensities within the same vertebral body. Semiautomatic segmentation methods have been employed to cope with this challenge. However, these methods require inside and outside annotation, which is not practical when analyzing a more significant number of exams. Aimed at minimizing the time spent on manual annotation, we proposed Fast INside Estimation (FINE), which automatically estimates the inside seeds based on the outside seeds. The experimental results with a representative dataset showed that FINE does not demand manual inside annotation, what the competitors methods do, and achieve higher Recall and Dice Score, on average, 97% and 96%, respectively. Higher Recall is particularly essential on features extraction and classification of VCFs. Therefore, FINE speeds up the manual annotation process while allowing more accurate semiautomatic segmentation. (AU)

• Processo FAPESP: 18/24414-2 - Ambiente para integração de técnicas para a extração de características e bases de dados complexos para o projeto MIVisBD
• Beneficiário: Mirela Teixeira Cazzolato
• Modalidade de apoio: Bolsas no Brasil - Programa Capacitação - Treinamento Técnico
• Processo FAPESP: 16/17078-0 - Mineração, indexação e visualização de Big Data no contexto de sistemas de apoio à decisão clínica (MIVisBD)
• Beneficiário: Agma Juci Machado Traina
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 17/23780-2 - Recuperação por conteúdo de imagens médicas para apoio a decisão clínica usando a abordagem radiômica
• Beneficiário: Jonathan da Silva Ramos
• Modalidade de apoio: Bolsas no Brasil - Doutorado