MIDAS - An Open-Source Toolkit for the Volumetric Measurement of CT Lung Lesions

An Open-Source Toolkit for the Volumetric Measurement of CT Lung Lesions

MIDAS/ISP: Lung Cancer Imaging/Article #123090

Title:

An Open-Source Toolkit for the Volumetric Measurement of CT Lung Lesions

Authors:

Ricardo S. Avila¹, Karthik Krishnan¹, Luis Ibanez¹, Wesley Turner¹, Julien Jomier¹

Institutions:

¹Kitware, Inc.

Publisher:

Optical Society of America

Publication date:

Received 2010-Jan-20

PDF Article:

123090.pdf

Abstract:

An open source lesion sizing toolkit has been developed with a general architecture for implementing lesion segmentation algorithms and a reference algorithm for segmenting solid and part-solid lesions in lung CT scans. The CT lung lesion segmentation algorithm detects four three-dimensional features corresponding to the lung wall, vasculature, lesion boundary edges, and low density background lung parenchyma. These features form boundaries and propagation zones that guide the evolution of a subsequent shape detection level set. User input is used to determine an initial seed point for the level set and users may also define a region of interest around the lesion. The methods are validated against 18 nodules using CT scans of an anthropomorphic thorax phantom simulating lung anatomy. The scans were acquired under differing scanner parameters to characterize algorithm behavior under varying acquisition scenarios. We also validated repeatability using six coffee-break (zero volume change) clinical cases. The source code, datasets, and a running application are all provided under an unrestrictive license to encourage reproducibility and foster scientific exchange.

Complete Data Collection & Article:

article_873_full.zip (601Mb)

Compressed Data Collection:

article_873_preview.zip (3Mb)

Data Collection:

View1	Fig. 2	Case001	Case001
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View4	Table 1	Case004	Case004
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View8	Table 1	Case008	Case008
View9	Table 1	Case009	Case009
View10	Fig. 5	Case010	Case010
View11	Fig. 6	Case011	Case011

OCIS Code:

110.2960 , 100.6890

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