FISICO: Fast Image SegmentatIon COrrection.

Autor: Waldo Valenzuela, Stephen J Ferguson, Dominika Ignasiak, Gaëlle Diserens, Levin Häni, Roland Wiest, Peter Vermathen, Chris Boesch, Mauricio Reyes
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: PLoS ONE, Vol 11, Iss 5, p e0156035 (2016)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0156035
Popis: BACKGROUND AND PURPOSE:In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis. METHODS:We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images. RESULTS:Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.
Databáze: Directory of Open Access Journals