Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas


Autoria(s): Alvarez, Matheus; Pina, Diana Rodrigues de; Giacomini, Guilherme; Romeiro, Fernando Gomes; Duarte, Sergio Barbosa; Yamashita, Seizo; Arruda Miranda, Jose Ricardo de; Ourselin, S.; Styner, M. A.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

03/12/2014

03/12/2014

01/01/2014

Resumo

Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.

Formato

9

Identificador

http://dx.doi.org/10.1117/12.2043822

Medical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.

0277-786X

http://hdl.handle.net/11449/112609

10.1117/12.2043822

WOS:000338543300155

WOS000338543300155.pdf

Idioma(s)

eng

Publicador

Spie - Int Soc Optical Engineering

Relação

Medical Imaging 2014: Image Processing

Direitos

closedAccess

Palavras-Chave #HCC #medical image segmentation #liver #medical imaging #computed tomography #image processing
Tipo

info:eu-repo/semantics/conferencePaper