A versatile method for bladder segmentation in computed tomography two-dimensional images under adverse conditions

• Tipo: Artigo em Revista Científica Internacional
• Data: 2017-09-01

Autores

João Ribeiro Pinto (Autor) FEUP; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine

Vol. 231 Nº 9

Páginas: 871-880

ISSN: 0954-4119

Editora: SAGE

Indexação

ISI Web of Knowledge - 2 Citações

ISI Web of Science

Scopus - 2 Citações

INSPEC

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências médicas e da saúde

Outras Informações

ID Authenticus: P-00N-ZW4

DOI: 10.1177/0954411917714294

Abstract (EN): This article presents the design and evaluation of an algorithm for urinary bladder segmentation in medical images, from contrastless computed tomography studies of patients suffering from bladder wall tumours. These situations require versatile methods of segmentation, able to adapt to the structural changes the tumours provoke in the bladder wall, reflected as irregularities on the images obtained, creating adversities to the segmentation process. This semi-automatic method uses fuzzy c-means clustering, a Gaussian-curve-based intensity transformation, and active contour models, requiring only the physician's input of a single seed point for each anatomical view, in order to segment the bladder volume in all frames that include it. The performance of the method was evaluated on eight patients of The Cancer Genome Atlas-Urothelial Bladder Carcinoma collection, achieving approximately 79% of successful segmentations for small tumour patients (below 2.0 cm of diameter) and approximately 72% between 2.0 and 2.9 cm. Successful segmentations for small tumour patients presented an average of 3.7 mm Hausdorff distance and 91.0% degree of overlap. The promising performance attained, especially for small tumour patients, revealed a high potential of this method to serve as basis for an effective early-stage bladder wall tumour computer-aided diagnosis system.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10