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On Simulating Subjective Evaluation Using Combined Objective Metrics for Validation of 3D Tumor Segmentation.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Ayache, Nicholas
Ourselin, Sébastien
Maeder, Anthony
Xiang Deng
Lei Zhu
Source :
Medical Image Computing & Computer-Assisted Intervention - MICCAI 2007; 2007, p977-984, 8p
Publication Year :
2007

Abstract

In this paper, we present a new segmentation evaluation method that can simulate radiologist's subjective assessment of 3D tumor segmentation in CT images. The method uses a new metric defined as a linear combination of a set of commonly used objective metrics. The weighing parameters of the linear combination are determined by maximizing the rank correlation between radiologist's subjective rating and objective measurements. Experimental results on 93 lesions demonstrate that the new composite metric shows better performance in segmentation evaluation than each individual objective metric. Also, segmentation rating using the composite metric compares well with radiologist's subjective evaluation. Our method has the potential to facilitate the development of new tumor segmentation algorithms and assist large scale segmentation evaluation studies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540757566
Database :
Complementary Index
Journal :
Medical Image Computing & Computer-Assisted Intervention - MICCAI 2007
Publication Type :
Book
Accession number :
34018655
Full Text :
https://doi.org/10.1007/978-3-540-75757-3_118